Information-seeking, curiosity, and attention: computational and neural mechanisms
Open accessAbstract
Summary Intelligent animals devote much time and energy to exploring and obtaining information, but the underlying mechanisms are poorly understood. We review recent developments on this topic that have emerged from the traditionally separate fields of machine learning, eye movements in natural behavior, and studies of curiosity in psychology and neuroscience. These studies show that exploration may be guided by a family of mechanisms that range from automatic biases toward novelty or surprise, to systematic search for learning progress and information gain in curiosity-driven behavior. In addition, eye movements reflect visual information search in multiple conditions and are amenable for cellular-level investigations, suggesting that the oculomotor system is an excellent model system for understanding information sampling mechanisms.
AI snapshot
Written from the paper’s full text.
TL;DR
This review integrates machine learning, eye-movement, and curiosity research to argue that information seeking ranges from automatic novelty/surprise biases to targeted search for learning progress and information gain. It proposes the oculomotor system as a model for information sampling and highlights intrinsic rewards and uncertainty monitoring as key open questions.
Key findings
- Information seeking is defined as actions whose primary goal is to obtain information and reduce uncertainty; it can be extrinsically motivated, as when a driver glances at a traffic light, or intrinsically motivated, as in curiosity or interest.
- Task-related gaze is proactively guided by uncertainty: in visuo-manual tasks the eyes move ahead of the hand to collision or target points and wait there, and in a virtual-reality walking study subjects preferentially deployed gaze to oncoming pedestrians with a history of veering onto a collision course.
- Curiosity-like mechanisms include Lowenstein’s information gap hypothesis, illustrated by a mystery novel with 10 equally likely suspects where the reader moves from high entropy to a single culprit, and developmental robotics approaches that reward learning progress rather than absolute competence.
- Novelty, surprise, and uncertainty heuristics help discover new tasks but are inefficient in large open-ended spaces and risk trapping agents in unlearnable tasks; learning-progress systems may support efficient exploration but a quantitative neural response to learning progress has not been demonstrated empirically.
Methods
- Narrative review synthesizing three traditionally separate lines: active learning and exploration in machine learning and robotics, eye movements in natural behavior, and curiosity in psychology and neuroscience.
- No primary empirical sample or new data are reported; the paper uses conceptual and computational examples, including a POMDP traffic-light example, the information gap mystery-novel illustration, and developmental robotics simulations/robots.
- Main analysis is conceptual integration and comparison of mechanisms across fields, not statistical meta-analysis.
Limitations
- The paper states that understanding information-seeking mechanisms is in its infancy, that a quantitative response to learning progress distinct from phasic responses to novelty, surprise, or arousal has not been demonstrated empirically, and that the learning-progress approach entails a complex meta-cognitive architecture awaiting empirical verification.
- The paper also states that it has not been empirically explored to what extent task-related informational eye movements are habitual, immutable aspects of a task versus rapidly responsive to changing epistemic conditions.
- Evident from the text: as a review, it provides no new experimental data, and many claims about intrinsic rewards and their neural implementation remain speculative; the paper itself notes the question of active exploration is vast and cannot be exhaustively covered.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 51 cited sources checked · 0 supported · 0 flagged
- Findingcitation
In well-practiced tasks involving visuo-manual coordination, the eyes move ahead of the hand to critical locations such as potential collision or target points and wait there until the hand has cleared those locations.
“In well-practiced tasks that involve visuo-manual coordination (such as moving an object to a target point) the eyes move ahead of the hand to critical locations such as potential collision or target points, and wait there until the hand has cleared those locations”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Johansson, Westling et al. 2001
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- Findingcitation
Computer simulations have shown that even if the objective fitness/reward function of an organism is to survive and reproduce, it may be more efficient to evolve a control architecture that encodes an innate surrogate reward function rewarding learning per se.
“Singh et al. (Singh, Lewis et al. 2010) have shown with computer simulations that even if the objective fitness/reward function of an organism is to survive and reproduce, it may be more efficient to evolve a control architecture that encodes an innate surrogate reward function rewarding learning per se.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Singh, Lewis et al. 2010
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- Findingcitation
Eye movement patterns made while acquiring a task differ greatly from those made after learning.
“Finally, the eye movements patterns made while acquiring a task differ greatly from those made after learning”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Sailer, Flanagan et al. 2005
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- cites Land 2006 source
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- Findingcitation
Observers preferentially deploy gaze to oncoming pedestrians whose trajectory is expected to be uncertain relative to those who have never shown such deviations.
“Subjects preferentially deployed gaze to oncoming pedestrians whose trajectory was expected to be uncertain (i.e., who had a history of veering onto a collision course) relative to those who had never shown such deviations.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Jovancevic-Misic and Hayhoe 2009
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- Findingcitation
Sensory novelty, defined as a small number of stimulus exposures, enhances neural responses throughout visual, frontal and temporal areas.
“Sensory novelty, defined as a small number of stimulus exposures, is known to enhance neural responses throughout visual, frontal and temporal areas”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Ranganath and Rainer 2003 source
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- Findingcitation
Sensory novelty activates reward-responsive dopamine-recipient areas.
“Sensory novelty, defined as a small number of stimulus exposures, is known to enhance neural responses throughout visual, frontal and temporal areas (Ranganath and Rainer 2003) and activate reward responsive dopamine-recipient areas.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Ranganath and Rainer 2003 source
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- Interpretationreasoning
Information seeking in its many manifestations is related to the ability of an observer to estimate his or her uncertainty and to find strategies that reduce that uncertainty.
“information seeking in its many manifestations is related to the ability of an observer to estimate his or her uncertainty and to find strategies that reduce that uncertainty.”
Quote in the paperSubstantial claim - Interpretationcitation
When deployed in the service of a task, eye movements may be explained by the simple imperative to sample information in order to reduce uncertainty regarding future states.
“Converging evidence suggests that, when deployed in the service of a task, eye movements may be explained by the simple imperative to sample information in order to reduce uncertainty regarding future states”
Quote in the paperSubstantial claim0 of 2 sources checked- cites Tatler, Hayhoe et al. 2011 source
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- cites Friston and Ao 2012
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- Premisenone given
Three lines of investigation-machine learning and robotics, eye movements in natural behavior, and curiosity in psychology and neuroscience-have remained largely separate.
“Our focus here is on evaluating recent developments related to this question from three lines of investigation that have remained largely separate – namely, studies of active learning and exploration in the machine learning and robotics fields, studies of eye movements in natural behavior, and studies of curiosity in psychology and neuroscience.”
Quote in the paperSubstantial claim - Premisecitation
Eye movements use value-based decision mechanisms.
“These observations, together with the fact that eye movements are well investigated at the single neuron level in experimental animals and use value-based decision mechanisms”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationreasoning
An observing action is only valuable if it increases the likelihood of reward of subsequent actions.
“It is clear from this POMDP-based analysis that, as an intermediate step in a sequence, an observing action is only valuable if it increases the likelihood of reward of subsequent actions.”
Quote in the paperSubstantial claim - Interpretationreasoning
By having an intrinsic motivation to learn, agents can maximize their long-term evolutionary fitness in rapidly changing environmental conditions.
“The most likely answer to the first, why question is that, by having an intrinsic motivation to learn, agents can maximize their long-term evolutionary fitness in rapidly changing environmental conditions”
Quote in the paperSubstantial claim - Interpretationreasoning
Eye movements are coupled with exploring for a task strategy.
“suggesting that eye movements are also coupled with exploring for a task strategy.”
Quote in the paperSubstantial claim - Interpretationreasoning
In real-world environments, many activities an agent can choose are inherently unlearnable either because of the learner's own limitations or because of irreducible uncertainty in the problem itself.
“in real world environments many of the activities that an agent can choose are inherently unlearnable either because of the learner’s own limitations or because of irreducible uncertainty in the problem itself.”
Quote in the paperSubstantial claim - Interpretationreasoning
The oculomotor system is an excellent model system for understanding information sampling mechanisms.
“suggesting that the oculomotor system is an excellent model system for understanding information sampling mechanisms.”
Quote in the paperNot a substantial claim - Interpretationreasoning
In the short term, an observing action delivers no reward but has a cost in time and effort.
“In the short term, the observing action delivers no reward but has a cost in terms of the time and effort needed to discriminate the information”
Quote in the paperSubstantial claim - Interpretationreasoning
Information value depends on the observer's momentary uncertainty.
“A second factor that determines information value is the observer’s momentary uncertainty.”
Quote in the paperSubstantial claim - Premisenone given
When an agent knows a task, the controllers implementing that task can select actions that harvest immediate rewards or actions with indirect benefits by facilitating future actions.
“Computational studies have shown that, when an agent knows a task, the controllers implementing that task can select actions that harvest immediate rewards, or actions that have indirect benefits by facilitating future actions.”
Quote in the paperSubstantial claim - Interpretationreasoning
The brain actively selects and proactively seeks out the information it wishes to sample.
“Far from being a passive recipient, the brain actively selects and proactively seeks out the information it wishes to sample”
Quote in the paperSubstantial claim - Interpretationreasoning
While sampling a very large space, the child must avoid becoming trapped in unlearnable situations where it cannot detect regularities or improve.
“A second salient fact regarding this question is that, while sampling this very large space, the child must avoid becoming trapped in unlearnable situations, i.e. where it cannot detect regularities or improve.”
Quote in the paperSubstantial claim - Interpretationreasoning
The cost of an observing action becomes worthwhile only if it transitions the agent to a better state, such that the cumulative future value of the better state exceeds that of the initial state by a sufficient amount.
“This cost becomes worthwhile only if the observing action transitions the agent to a better state - i.e., if the cumulative future value of state xb exceeds that of state xa by a sufficient amount.”
Quote in the paperSubstantial claim - Interpretationreasoning
Whether information sampling has positive value depends on the observer knowing the significance of the information and using it to plan future actions.
“Whether or not information sampling has positive value depends on two factors. First, the observer must know the significance of the information and use it to plan future actions.”
Quote in the paperSubstantial claim - Premisecitation
Making the environment predictable, through minimizing the dispersion of its hidden states, necessarily entails actions that decrease uncertainty about future states.
“In fact, it is possible to show that making the environment predictable (through minimizing the dispersion of its hidden states) necessarily entails actions that decrease uncertainty about future states”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Friston, Thornton et al. 2012
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- Interpretationcitation
The active control of eye movements makes it clear that information sampling is a highly active process.
“the active control of eye movements makes it clear that information sampling is a highly active process”
Quote in the paperSubstantial claim - Premisereasoning
In extrinsically motivated contexts, information gathering is a means to an end used to maximize progress toward a separate goal.
“In extrinsically motivated contexts, information gathering is a means to an end – i.e., it is used to maximize the agent’s progress toward a separate goal.”
Quote in the paperNot a substantial claim - Premisenone given
In foveate animals such as humans and monkeys, visual information is sampled by eye movements, particularly saccades.
“In foveate animals such as humans and monkeys, visual information is sampled by means of eye movements, and in particular saccades”
Quote in the paperSubstantial claim - Interpretationreasoning
Uncertainty and information value are not defined unless observers have prior knowledge of the links between stimuli and actions.
“This makes the strong computational point that uncertainty and information value are not defined unless observers have prior knowledge of the links between stimuli and actions.”
Quote in the paperSubstantial claim - Premisecitation
In the sensorimotor domain, a child needs to learn to generate an enormous repertoire of movements by orchestrating multiple interdependent muscles and joints that interact in a potentially infinite number of ways with a vast number of physical objects or situations.
“In the sensorimotor domain alone, and in spite of significant innate constraints, the child needs to learn to generate an enormous repertoire of movements by orchestrating multiple interdependent muscles and joints that can be accessed at many hierarchical levels and interact in a potentially infinite number of ways with a vast number of physical objects/situations”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Oudeyer, Baranes et al. 2013
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- Interpretationreasoning
Intrinsically motivated cognitive activities, including information seeking, acquired value through long-term evolutionary selection in dynamic conditions.
“In one way or another, all these formulations are consistent with the idea that intrinsically motivated cognitive activities, including information seeking, acquired value through long-term evolutionary selection in dynamic conditions.”
Quote in the paperNot a substantial claim - Interpretationnone given
Exploration may be guided by a family of mechanisms ranging from automatic biases toward novelty or surprise to systematic search for learning progress and information gain in curiosity-driven behavior.
“These studies show that exploration may be guided by a family of mechanisms that range from automatic biases toward novelty or surprise, to systematic search for learning progress and information gain in curiosity-driven behavior.”
Quote in the paperSubstantial claim - Premisenone given
Many strategy-learning methods can be seen as a POMDP whose uncertainty is on the task parameters themselves rather than on the task-relevant state.
“Many of these methods can be seen as a POMDP whose uncertainty is not on the task-relevant state but on the task parameters themselves.”
Quote in the paperNot a substantial claim - Premisecitation
The progress-based approach has been used most successfully in real-world situations.
“This progress-based approach has been used most successfully in real-world situations.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites L. Pape 2012 source
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- cites Ngo, Luciw et al. 2012
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- cites Baranes and Oudeyer 2013
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- Interpretationreasoning
The learning-progress approach entails a complex meta-cognitive architecture for monitoring learning progress that still awaits empirical verification.
“It must be noted however that, while computationally powerful, this approach entails a complex meta-cognitive architecture for monitoring learning progress that still awaits empirical verification.”
Quote in the paperNot a substantial claim - Premisecitation
Heuristics based on novelty can guide efficient learning in small and closed spaces, where the number of tasks is small.
“Therefore, heuristics based on novelty can guide efficient learning in small and closed spaces, where the number of tasks is small (Thrun 1995)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Thrun 1995
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- Premisecitation
An alternative mechanism for targeted learning has been proposed in developmental robotics, which tracks an agent's local learning progress without setting an absolute goal.
“An alternative mechanism for targeted learning has been proposed in the field of developmental robotics, which eschews this difficulty by tracking an agent’s local learning progress without setting an absolute goal (Oudeyer, Kaplan et al. 2007; Oudeyer, Baranes et al. 2013; Schmidhuber 2013)”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites Oudeyer, Kaplan et al. 2007
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- cites Oudeyer, Baranes et al. 2013
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- cites Schmidhuber 2013
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- Rests on an assumption: The central objective of developmental robotics is to design agents that can explore in open-ended environments and develop autonomously without a pre-programmed trajectory, based on their intrinsic interest.
- Premisecitation
Novelty acts as an intrinsic reward for actions and states that had not been recently explored or that produce high empirical prediction errors.
“This is consistent with the theoretical notion that novelty acts as an intrinsic reward for actions and states that had not been recently explored or that produce high empirical prediction errors”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Duzel, Bunzeck et al. 2010 source
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- Premisecitation
Heuristics based on novelty are very inefficient in large open-ended spaces, where they only allow the agent to collect very sparse data and risk trapping him in unlearnable tasks.
“but are very inefficient in large open ended spaces, where they only allow the agent to collect very sparse data and risk trapping him in unlearnable tasks (Oudeyer, Kaplan et al. 2007; Oudeyer, Baranes et al. 2013; Schmidhuber 2013).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Oudeyer, Kaplan et al. 2007
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- cites Oudeyer, Baranes et al. 2013
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- cites Schmidhuber 2013
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- Interpretationreasoning
One cannot be curious about what one does not know.
“In other words, one cannot be curious about what one does not know, similar to the requirements for prior knowledge of stimulus-action links that arise in eye movement control (Fig. 1).”
Quote in the paperSubstantial claim - Interpretationreasoning
A system based on learning progress holds promise for achieving efficient, intrinsically motivated exploration in large open-ended spaces.
“In sum, a system based on learning progress holds promise for achieving efficient, intrinsically motivated exploration in large open-ended spaces.”
Quote in the paperSubstantial claim - Premisecitation
The progress-based approach was shown to spontaneously lead a robot to discover vocal communication with a peer, while traversing stages of babbling that resemble those of infants.
“Initially applied to sensorimotor tasks such as object manipulation, the approach was also shown to spontaneously lead a robot to discover vocal communication with a peer (while traversing stages of babbling that resemble those of infants as a consequence of its drive to explore situations which the learner estimates to be learnable (Oudeyer and Kaplan 2006; Moulin-Frier and Oudeyer 2012)).”
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- cites Moulin-Frier and Oudeyer 2012
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- Interpretationreasoning
Recognizing and eliminating information gaps requires a radically different, knowledge-based mechanism than biological drives.
“It is important to recognize, however, that, while biological drives are prompted by salient and easily recognizable signs (e.g., somatic signals for hunger or sex), recognizing and eliminating information gaps requires a radically different, knowledge-based mechanism.”
Quote in the paperSubstantial claim- Rests on an assumption: Biological drives are prompted by salient and easily recognizable signs.
- Interpretationreasoning
By using a local measure of learning, the learning-progress system avoids difficulties associated with defining an absolute competence or epistemic goal.
“By using a local measure of learning the system avoids difficulties associated with defining an absolute (and potentially unknowable) competence or epistemic goal.”
Quote in the paperSubstantial claim - Interpretationreasoning
Similar to an information gap mechanism, the learning-progress system produces a targeted search for information that drives the agent to learn.
“Similar to an information gap mechanism, this system produces a targeted search for information that drives the agent to learn.”
Quote in the paperNot a substantial claim - Interpretationreasoning
A potential limitation of the information gap hypothesis is that agents may not be able to estimate the starting or desired levels of uncertainty given their necessarily limited knowledge of the broader context.
“Despite its considerable strengths, a potential limitation of the information gap hypothesis is that agents may not be able to estimate the starting or desired levels of uncertainty given their necessarily limited knowledge of the broader context.”
Quote in the paperNot a substantial claim- Rests on an assumption: In scientific research, the results of an experiment typically open up new questions that had not been foreseen, and it is not possible to estimate in advance the current entropy and the final desired state.
- Interpretationreasoning
A quantitative response to learning progress, distinct from phasic responses to novelty, surprise or arousal, has not been demonstrated in empirical investigations.
“However, a quantitative response to learning progress (which is distinct from phasic responses to novelty, surprise or arousal) has not been demonstrated in empirical investigations.”
Quote in the paperNot a substantial claim - Interpretationreasoning
An agent needs some prior knowledge in order to set the starting and reference points of an information gap.
“First, the agent needs some prior knowledge in order to set the starting and the reference points.”
Quote in the paperSubstantial claim - Interpretationreasoning
Actions driven by randomness, novelty, uncertainty or surprise do not guarantee that an agent will learn.
“However, these actions have an important limitation in that they do not guarantee that an agent will learn.”
Quote in the paperSubstantial claim - Interpretationreasoning
The mere fact that an event is novel or surprising does not guarantee that it contains regularities that are detectable, generalizable or useful.
“The mere fact that an event is novel or surprising does not guarantee that it contains regularities that are detectable, generalizable or useful.”
Quote in the paperSubstantial claim - Premisecitation
The learning-progress system self-organizes development and learning trajectories that share fundamental qualitative properties with infant development, in particular the gradual shift of interest from simpler to more complex skills.
“Second, the system self-organizes development and learning trajectories that share fundamental qualitative properties with infant development, in particular the gradual shift of interest from simpler to more complex skills (Oudeyer and Kaplan 2006; Oudeyer, Kaplan et al. 2007; Kaplan and Oudeyer 2011; Moulin-Frier and Oudeyer 2012) (Fig. 2).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Oudeyer and Kaplan 2006
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- cites Oudeyer, Kaplan et al. 2007
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- cites Kaplan and Oudeyer 2011
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- Premisecitation
Computational models have incorporated uncertainty-based strategies, generating biases toward actions or states that have high variance or entropy.
“Computational models have also incorporated uncertainty-based strategies, generating biases toward actions or states that have high variance or entropy”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Cohn, Ghahramani et al. 1996
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- cites Rothkopf and Ballard 2010
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- Interpretationcitation
Possible candidates for a meta-cognitive system for monitoring learning progress include frontal systems that encode uncertainty or confidence in humans and monkeys.
“Possible candidates for such a system include frontal systems that encode the uncertainty or confidence in humans and monkeys (Fleming, Weil et al. 2010; Fleming, Huijgen et al. 2012; De Martino, Fleming et al. 2013)”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisecitation
The progress-based approach allows robots to efficiently learn repertoires of skills in high dimensions and under strong time constraints.
“First, it allows robots to efficiently learn repertoires of skills in high dimensions and under strong time constraints”
Quote in the paperSubstantial claim0 of 3 sources checked- cites L. Pape 2012 source
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- cites Ngo, Luciw et al. 2012
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- cites Baranes and Oudeyer 2013
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- Premisecitation
The progress-based approach allows robots to avoid unfruitful activities that are either well learnt and trivial, or which are random and unlearnable.
“and to avoid unfruitful activities that are either well learnt and trivial, or which are random and unlearnable (L. Pape 2012; Ngo, Luciw et al. 2012; Baranes and Oudeyer 2013; Nguyen and Oudeyer 2013).”
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- cites Ngo, Luciw et al. 2012
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- cites Baranes and Oudeyer 2013
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- Premisenone given
Actions driven by randomness, novelty, uncertainty or surprise are valuable for allowing agents to discover new tasks.
“As discussed above, actions driven by randomness, novelty, uncertainty or surprise are valuable for allowing agents to discover new tasks.”
Quote in the paperSubstantial claim - Interpretationreasoning
The information gap theory links the study of epistemically-based action systems with that of motivated behaviors.
“Thus, the information gap theory links the study of epistemically-based action systems with that of motivated behaviors.”
Quote in the paperSubstantial claim
- May combine two claims. 12
- Classified as probably not a substantial claim. 22
May combine two claims.
FindingreasoningThe eyes never track the hand; instead they are strategically deployed to acquire new information.
“Notably, the eyes never track the hand, which relies on motor and proprioceptive guidance and, for short periods of time, follows a predictable path; instead, they are strategically deployed to acquire new information.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisereasoningThe learning space is vast, especially given the scarce time and energy available for learning.
“One salient fact that emerges regarding this question is the sheer vastness of the learning space, especially given the scarce time and energy available for learning.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenDeciding how to explore optimally when searching for a strategy is very difficult and almost intractable in the general case.
“Deciding how to explore optimally when searching for strategy is a very difficult question, and is almost intractable in the general case.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Premisenone givenA number of processes for open-ended exploration have been described that have individual strengths and weaknesses and may act in complementary fashion to accomplish the goals of information seeking.
“A number of processes for open-ended exploration have been described in the literature, which, as we describe below, have individual strengths and weaknesses and may act in complementary fashion to accomplish these goals.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable).
PremisereasoningInformation gathering actions are a special type of intermediate step that obey the imperative to reduce uncertainty and adjudicate among competing interpretations.
“Information gathering actions are a special type of intermediate step that obey the imperative to reduce uncertainty and adjudicate among competing interpretations.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationObservers monitor the uncertainty or predictability of external items and use these quantities proactively to deploy gaze.
“This suggests that the observers monitor the uncertainty or predictability of external items and use these quantities proactively to deploy gaze”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenStrategies for solving a task, including those for generating informational actions, are not known in advance but must be learnt.
“Strategies for solving a task, including those for generating informational actions, are not known in advance but must also be learnt.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningStrategy-learning processes require significant exploration but are goal directed in that they seek to maximize a separate, extrinsic reward.
“It is important to note that, while these processes require significant exploration, they are goal directed in the sense that they seek to maximize a separate, or extrinsic, reward”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe challenge of an information seeking mechanism is to learn efficiently a large repertoire of diverse skills given limited resources, and to avoid being trapped in unlearnable situations.
“Thus, the challenge of an information seeking mechanism is to learn efficiently a large repertoire of diverse skills given its limited resources, and avoid being trapped in unlearnable situations.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenIn the cognitive domain, infants must acquire a vast amount of factual knowledge, rules and social skills.
“Similarly in the cognitive domain, infants must acquire a vast amount of factual knowledge, rules and social skills.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenThe three lines of research on information seeking grapple with strikingly similar questions and propose overlapping mechanisms.
“although using different terminology and methods, these three lines of research grapple with strikingly similar questions and propose overlapping mechanisms.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationcitationThe benefits of an intrinsic learning reward arise because of the limited cognitive capacities of the agent or because information or skills that are not immediately useful may be re-used in the future.
“The benefits of such a system arise because of the limited cognitive capacities of the agent (i.e., its inability to solve the fitness function directly) (Sorg, Lewis et al. 2010; Lehman and Stanley 2011; Sequeira, Melo et al. 2011) or because information or skills that are not immediately useful may be re-used in the future.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Sorg, Lewis et al. 2010
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- cites Lehman and Stanley 2011
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- cites Sequeira, Melo et al. 2011
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Classified as probably not a substantial claim.
PremisereasoningExploratory actions are distinct from other motor acts in that their primary goal is not to exert force on the world but to alter the observer's epistemic state.
“Although exploratory actions can involve physical acts, they are distinct from other motor acts in that their primary goal is not to exert force on the world, but to alter the observer’s epistemic state.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationnone givenEye movements reflect visual information search in multiple conditions and are amenable to cellular-level investigations.
“eye movements reflect visual information search in multiple conditions and are amenable for cellular-level investigations”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisenone givenIn intrinsically motivated contexts, the search for information is a goal in itself, a process called curiosity or interest.
“In intrinsically motivated contexts, on the other hand, the search for information is a goal in itself – a process we would intuitively call “curiosity” or “interest”.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
InterpretationreasoningThe fact that animals and humans seek information without an apparent ulterior motive suggests that the brain generates intrinsic rewards that assign value to information.
“The fact that animals, and particularly humans, seem avidly to seek out information without an apparent ulterior motive suggests that the brain generates intrinsic rewards that assign value to information”
Quote in the paperNot a substantial claim- The authors state this as an assumption: The brain generates intrinsic rewards related to learning or acquiring information.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe free-energy principle states that the possession of a large array of skills can be useful to avoid future surprises by anticipating a changing and itinerant world.
“This idea resonates with the free-energy principle, which states that the possession of a large array of skills can be useful to avoid future surprises by “anticipating a changing and itinerant world””
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Friston 2010 source
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- cites Friston, Thornton et al. 2012
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PremisecitationContextual novelty, also called surprise, has been suggested to account for attentional attraction toward salient events.
“A more complex form of “contextual novelty” (also called surprise) has been suggested to account for attentional attraction toward salient events”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Boehnke, Berg et al. 2011
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PremisecitationContextual novelty may be quantified using Bayesian inference as a difference between a prior and posterior world model or as a high prediction error for high-confidence states.
“may be quantified using Bayesian inference as a difference between a prior and posterior world model (Itti and Baldi 2009) or as a high prediction error for high-confidence states (Oudeyer and Kaplan 2007).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Itti and Baldi 2009 source
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- cites Oudeyer and Kaplan 2007
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InterpretationreasoningAnimals seek to fill gaps in their physical resources and seek to fill gaps in their knowledge by taking learning-oriented actions.
“Just as animals seek to fill gaps in their physical resources (e.g., energy, sex or wealth) they seek to fill gaps in their knowledge by taking learning-oriented actions.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenIn neuroscience research, the most commonly considered exploration strategies are based on random action selection or automatic biases toward novel, surprising or uncertain events.
“In neuroscience research, the most commonly considered exploration strategies are based on random action selection or automatic biases toward novel, surprising or uncertain events.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningCuriosity can be viewed as a deprivation phenomenon that seeks to fill a need similar to other reference-point phenomena or biological drives.
“Defined in this way, curiosity can be viewed as a deprivation phenomenon that seeks to fill a need similar to other reference-point phenomena or biological drives.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
InterpretationreasoningThe imperative to minimize uncertainty about the state of the world is similar to a biological drive.
“This brings us back again to the imperative to minimize uncertainty about the state of the world, and suggests that this imperative is similar to a biological drive.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
InterpretationreasoningTo define an information gap one has to monitor one's level of uncertainty.
“Second, to define an information gap one has to monitor one’s level of uncertainty, again similar to eye movement control.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenUnderstanding information seeking requires understanding how agents monitor their own competence and epistemic states, and specifically how they estimate their uncertainty and generate strategies for reducing that uncertainty.
“First, understanding information seeking requires that we understand how agents monitor their own competence and epistemic states, and specifically how they estimate their uncertainty and generate strategies for reducing that uncertainty.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenEye movements are natural indicators of the brain's active information search.
“Finally, eye movements are natural indicators of the brain’s active information search.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationSpecific epistemic curiosity arises because of a discrepancy between what the observer knows and what he would like to know, where knowledge can be measured with traditional measures of information.
“According to the information gap theory, this type of curiosity arises because of a discrepancy between what the observer knows and what he would like to know, where knowledge can be measured with traditional measures of information.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Lowenstein 1994 source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenUnderstanding information seeking requires understanding the nature of intrinsic rewards that motivate information seeking and learning.
“Second, this question requires that we understand the nature of intrinsic rewards that motivate information seeking and learning.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable). May combine two claims.
InterpretationreasoningEye movements may be an excellent model system for tackling the question of active exploration, especially if studied in conjunction with computational approaches and the brain's intrinsic reward and cognitive control mechanisms.
“By virtue of their amenability to neurophysiological investigations, may be an excellent model system for tackling this question, especially if studied in conjunction with computational approaches and the brain’s intrinsic reward and cognitive control mechanisms.”
Quote in the paperNot a substantial claim- Rests on an assumption: The brain has intrinsic reward and cognitive control mechanisms.
- Rests on an assumption: Eye movements are amenable to neurophysiological investigations.
Probably not a substantial claim: may not pass S3 (load-bearing).
InterpretationcitationPossible candidates for a meta-cognitive system for monitoring learning progress include frontal systems that respond selectively for behavioral change or the beginning of exploratory episodes.
“or which respond selectively for behavioral change or the beginning of exploratory episodes (Isoda and Hikosaka 2007; Quilodran, Rothe et al. 2008).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Isoda and Hikosaka 2007
Not checked in the free run.
- cites Quilodran, Rothe et al. 2008
Not checked in the free run.
The authors state this as an assumption.
The brain generates intrinsic rewards related to learning or acquiring information.
“it seems necessary to assume that the brain generates intrinsic rewards related to learning or acquiring information (Berlyne 1960).”
The paper relies on this without support.
Biological drives are prompted by salient and easily recognizable signs.
“while biological drives are prompted by salient and easily recognizable signs (e.g., somatic signals for hunger or sex)”
The paper relies on this without support.
In scientific research, the results of an experiment typically open up new questions that had not been foreseen, and it is not possible to estimate in advance the current entropy and the final desired state.
“In scientific research for example, the results of an experiment typically open up new questions that had not been foreseen, and it is not possible to estimate in advance what is the current entropy and the final, desired, state.”
The paper relies on this without support.
The central objective of developmental robotics is to design agents that can explore in open-ended environments and develop autonomously without a pre-programmed trajectory, based on their intrinsic interest.
“The central objective of developmental robotics is to design agents that can explore in open-ended environments and develop autonomously without a pre-programmed trajectory, based on their intrinsic interest.”
The paper relies on this without support.
The brain has intrinsic reward and cognitive control mechanisms.
“the brain’s intrinsic reward and cognitive control mechanisms.”
The paper relies on this without support.
Eye movements are amenable to neurophysiological investigations.
“By virtue of their amenability to neurophysiological investigations”
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Self-citationA Neural Correlate of Motivational Conflict in the Superior Colliculus of the Macaque
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Learning skills from play: Artificial curiosity on a Katana robot arm
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Self-citationEmerging social awareness: Exploring intrinsic motivation in multiagent learning
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Exploration from Generalization Mediated by Multiple Controllers
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Maximizing Fun by Creating Data with Easily Reducible Subjective Complexity
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“An alternative mechanism for targeted learning has been proposed in the field of developmental robotics, which eschews this difficulty by tracking an agent’s local learning progress without setting an absolute goal (Oudeyer, Kaplan et al. 2007; Oudeyer, Baranes et al. 2013; Schmidhuber 2013) (following an early formul…”
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Self-citationHogarth, L., Dickinson, A., & Duka, T. (2010) · Open Research Exeter (University of Exeter) · Cited by 9 · see citing works
First Experiments with PowerPlayPreprint
Srivastava, R. K., Steunebrink, B. R., & Schmidhuber, J. (2012) · arXiv (Cornell University) · doi:10.48550/arxiv.1210.8385 · Cited by 7 · see citing works
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Continual lifelong learning with neural networks: A review
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The Psychology and Neuroscience of Curiosity
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What is consciousness, and could machines have it?
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Electronic skins and machine learning for intelligent soft robots
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The Emerging Neuroscience of Intrinsic Motivation: A New Frontier in Self-Determination Research
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Towards a neuroscience of active sampling and curiosity
Gottlieb, J., & Oudeyer, P.-Y. (2018) · Nature Reviews Neuroscience · doi:10.1038/s41583-018-0078-0 · Cited by 494 · see citing works
Self-citationIntrinsic motivation, curiosity, and learning
Oudeyer, P., Gottlieb, J. P., & Lopes, M. C. (2016) · Progress in brain research · doi:10.1016/bs.pbr.2016.05.005 · Cited by 390 · see citing works
Self-citationProcess Account of Curiosity and Interest: A Reward-Learning Perspective
Murayama, K., FitzGibbon, L., & Sakaki, M. (2019) · Educational Psychology Review · doi:10.1007/s10648-019-09499-9 · Cited by 306 · see citing works
Attention in Psychology, Neuroscience, and Machine Learning
Lindsay, G. W. (2020) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2020.00029 · Cited by 320 · see citing works
“An additional factor that drives biological attention but is perhaps underrepresented in artificial attention systems is curiosity (Gottlieb et al., 2013).”
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“This drive for information is poorly understood, but is relevant for understanding learning, decision making, and social interactions (Gottlieb et al., 2013).”
Gruber, M. J., & Charan Ranganath, A. (2019) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2019.10.003 · Cited by 264 · see citing works
Computational mechanisms of curiosity and goal-directed exploration
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Predictability and Uncertainty in the Pleasure of Music: A Reward for Learning?
Gold, B. P., Pearce, M. T., Herrero, E. M., Dagher, A., & Zatorre, R. J. (2019) · Journal of Neuroscience · doi:10.1523/jneurosci.0428-19.2019 · Cited by 254 · see citing works
Developmental process emerges from extended brain–body–behavior networks
Byrge, L. A., Sporns, O., & Smith, L. B. (2014) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2014.04.010 · Cited by 212 · see citing works
Brain adaptation and alternative developmental trajectories
Johnson, M. H., Jones, E. J. H., & Gliga, T. (2015) · Development and Psychopathology · doi:10.1017/s0954579415000073 · Cited by 213 · see citing works
Homo Curious: Curious or Interested?
Shin, D. D., & Kim, S. (2019) · Educational Psychology Review · doi:10.1007/s10648-019-09497-x · Cited by 206 · see citing works
How Evolution May Work Through Curiosity‐Driven Developmental Process
Oudeyer, P., & Smith, L. B. (2016) · Topics in Cognitive Science · doi:10.1111/tops.12196 · Cited by 192 · see citing works
Self-citationLevin, M. (2022) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2022.768201 · Cited by 195 · see citing works
Infants’ preferences for native speakers are associated with an expectation of information
Begus, K., Gliga, T., & Southgate, V. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1603261113 · Cited by 181 · see citing works
Overconfidence among beginners: Is a little learning a dangerous thing?
Sanchez, C., & Dunning, D. (2018) · Journal of Personality and Social Psychology · doi:10.1037/pspa0000102 · Cited by 177 · see citing works
Diverse motives for human curiosity
Kobayashi, K., Ravaioli, S., Baranès, A., Woodford, M., & Gottlieb, J. P. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0589-3 · Cited by 157 · see citing works
Self-citationInduction and Relief of Curiosity Elicit Parietal and Frontal Activity
van Lieshout, L. L. F., Vandenbroucke, A. R. E., Müller, N. C. J., Cools, R., & de Lange, F. P. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.2816-17.2018 · Cited by 151 · see citing works
Moulin-Frier, C., Nguyen, S., & Oudeyer, P. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2013.01006 · Cited by 172 · see citing works
Self-citationDuan, H., Fernández, G., van Dongen, E. V., & Kohn, N. (2020) · Brain Structure and Function · doi:10.1007/s00429-020-02074-x · Cited by 170 · see citing works
“Curiosity is then induced through individuals’ awareness of the discrepancy between their current informational and goal uncertainty states (Gottlieb et al. 2013).”
Common neural code for reward and information value
Kobayashi, K., & Hsu, M. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1820145116 · Cited by 148 · see citing works
The feeling of grip: novelty, error dynamics, and the predictive brain
Kiverstein, J., Miller, M., & Rietveld, E. (2019) · Synthese · doi:10.1007/s11229-017-1583-9 · Cited by 143 · see citing works
The rhythm of learning: Theta oscillations as an index of active learning in infancy
Begus, K., & Bonawitz, E. B. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100810 · Cited by 148 · see citing works
Eye movements reveal epistemic curiosity in human observers
Baranès, A., Oudeyer, P., & Gottlieb, J. P. (2015) · Vision Research · doi:10.1016/j.visres.2015.10.009 · Cited by 136 · see citing works
Self-citationInterest Development and Its Relation to Curiosity: Needed Neuroscientific Research
Hidi, S. E., & Renninger, K. A. (2019) · Educational Psychology Review · doi:10.1007/s10648-019-09491-3 · Cited by 137 · see citing works
Fixation patterns in simple choice reflect optimal information sampling
Callaway, F., Rangel, A., & Griffiths, T. L. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008863 · Cited by 141 · see citing works
Curiosity in old age: A possible key to achieving adaptive aging
Sakaki, M., Yagi, A., & Murayama, K. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.03.007 · Cited by 139 · see citing works
Infants tailor their attention to maximize learning
Poli, F., Serino, G., Mars, R. B., & Hunnius, S. (2020) · Science Advances · doi:10.1126/sciadv.abb5053 · Cited by 120 · see citing works
Theoretical perspectives on active sensing
Yang, S. C., Wolpert, D. M., & Lengyel, M. (2016) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2016.06.009 · Cited by 119 · see citing works
Shared striatal activity in decisions to satisfy curiosity and hunger at the risk of electric shocks
Lau, J. K. L., Ozono, H., Kuratomi, K., Komiya, A., & Murayama, K. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-0848-3 · Cited by 124 · see citing works
“Our results showed that (1) both curiosity for inconsequential knowledge (magic tricks or trivia questions) and hunger for food prompted participants to subject themselves to physical risks (that is, electric shocks), and (2) this motivated decision-making was supported by the striatal reward areas.”
InfluentialInterest Development and Learning
Renninger, K. A., & Hidi, S. E. (2019) · Cambridge University Press eBooks · doi:10.1017/9781316823279.013 · Cited by 136 · see citing works
Development of directed and random exploration in children
Meder, B., Wu, C. M., Schulz, E., & Ruggeri, A. (2021) · Developmental Science · doi:10.1111/desc.13095 · Cited by 114 · see citing works
How Are Curiosity and Interest Different? Naïve Bayes Classification of People’s Beliefs
Donnellan, E., Aslan, S., Fastrich, G. M., & Murayama, K. (2021) · Educational Psychology Review · doi:10.1007/s10648-021-09622-9 · Cited by 125 · see citing works
Interest development, self-related information processing, and practice
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The modulation of savouring by prediction error and its effects on choice
Iigaya, K., Story, G. W., Kurth-Nelson, Z. L., Dolan, R. J., & Dayan, P. (2016) · eLife · doi:10.7554/elife.13747 · Cited by 110 · see citing works
Anterior Cingulate Cortex and the Control of Dynamic Behavior in Primates
Monosov, I. E., Haber, S. N., Leuthardt, E. C., & Jezzini, A. (2020) · Current Biology · doi:10.1016/j.cub.2020.10.009 · Cited by 118 · see citing works
Midcingulate Motor Map and Feedback Detection: Converging Data from Humans and Monkeys
Procyk, E., Wilson, C. R. E., Stoll, F. M., Faraut, M. C. M., Petrides, M., & Amiez, C. (2014) · Cerebral Cortex · doi:10.1093/cercor/bhu213 · Cited by 122 · see citing works
“Indeed, eye movements are major tools for information-seeking in primates (Gottlieb et al. 2013).”
Hunters, busybodies and the knowledge network building associated with deprivation curiosity
Lydon‐Staley, D. M., Zhou, D., Sizemore, A. E., Zurn, P., & Bassett, D. S. (2020) · Nature Human Behaviour · doi:10.1038/s41562-020-00985-7 · Cited by 109 · see citing works
Play in predictive minds: A cognitive theory of play.
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Spontaneous Metacognition in Rhesus Monkeys
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Individual differences in information-seeking
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From relief to surprise: Dual control of epistemic curiosity in the human brain
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Adaptive Robot Language Tutoring Based on Bayesian Knowledge Tracing and Predictive Decision-Making
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States of curiosity and interest enhance memory differently in adolescents and in children
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To Level the Playing Field, Develop Interest
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Multi-Armed Bandits for Intelligent Tutoring SystemsPreprint
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Self-citationThe Educational Benefits of Self-Related Information Processing
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Relating Pupil Dilation and Metacognitive Confidence during Auditory Decision-Making
Lempert, K. M., Chen, Y. L., & Fleming, S. M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0126588 · Cited by 94 · see citing works
Play, Curiosity, and Cognition
Chu, J., & Schulz, L. E. (2020) · Annual Review of Developmental Psychology · doi:10.1146/annurev-devpsych-070120-014806 · Cited by 93 · see citing works
The Double-Edged Sword of Big Data in Organizational and Management Research
Wenzel, R., & Quaquebeke, N. V. (2017) · Organizational Research Methods · doi:10.1177/1094428117718627 · Cited by 104 · see citing works
“…affective arousal via physiological reactions in employees (e.g., pulse, skin conductance; Becker & Menges, 2013) and information-seeking via visuospatial attention on their computer screens (e.g., eye fixation, gaze patterns; Gottlieb, Oudeyer, Lopes, & Baranes, 2013; Hoffman & Subramaniam, 1995).”
Visual Saliency-Aware Receding Horizon Autonomous Exploration with Application to Aerial Robotics
Dang, T., Papachristos, C., & Alexis, K. (2018) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2018.8460992 · Cited by 97 · see citing works
The Demand for, and Avoidance of, Information
Golman, R., Loewenstein, G. F., Molnár, A., & Saccardo, S. (2021) · Management Science · doi:10.1287/mnsc.2021.4244 · Cited by 97 · see citing works
Curiosity‐based learning in infants: a neurocomputational approach
Twomey, K. E., & Westermann, G. (2017) · Developmental Science · doi:10.1111/desc.12629 · Cited by 93 · see citing works
Humans monitor learning progress in curiosity-driven exploration
Ten, A., Kaushik, P., Oudeyer, P. Y., & Gottlieb, J. P. (2021) · Nature Communications · doi:10.1038/s41467-021-26196-w · Cited by 97 · see citing works
“C uriosity, our desire to know, is a fundamental drive in human behavior and a topic of renewed interest in neuroscience and cognitive psychology 1,2 . of recent The vast majority research on curiosity has operationalized it as intrinsically motivated information demand, using tasks in which…”
Self-citationYoo, S. B. M., Hayden, B. Y., & Pearson, J. M. (2021) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2019.0664 · Cited by 93 · see citing works
Managerial academic experience, external monitoring and financial reporting quality
Ma, Z., Novoselov, K. E., Zhou, K., & Zhou, Y. X. (2019) · Journal of Business Finance & Accounting · doi:10.1111/jbfa.12398 · Cited by 95 · see citing works
How Outcome Uncertainty Mediates Attention, Learning, and Decision-Making
Monosov, I. E. (2020) · Trends in Neurosciences · doi:10.1016/j.tins.2020.06.009 · Cited by 87 · see citing works
Bazhydai, M., Westermann, G., & Parise, E. (2020) · Developmental Science · doi:10.1111/desc.12938 · Cited by 85 · see citing works
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Self-citationRethinking employability: how students build on interest in a subject to plan a career
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Curiosity as a Metacognitive Feeling
Goupil, L., & Proust, J. (2023) · Cognition · doi:10.1016/j.cognition.2022.105325 · Cited by 89 · see citing works
Energization and Direction Are Both Essential Parts of Motivation
Elliot, A. J. (2023) · Oxford University Press eBooks · doi:10.1093/oso/9780197662359.003.0002 · Cited by 91 · see citing works
Baranès, A., Oudeyer, P., & Gottlieb, J. P. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00317 · Cited by 85 · see citing works
Self-citationState estimation in posterior parietal cortex: Distinct poles of environmental and bodily states
Medendorp, W. P., & Heed, T. (2019) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2019.101691 · Cited by 84 · see citing works
A functional approach to explanation-seeking curiosity
Liquin, E. G., & Lombrozo, T. (2020) · Cognitive Psychology · doi:10.1016/j.cogpsych.2020.101276 · Cited by 79 · see citing works
Specific frontal neural dynamics contribute to decisions to check
Stoll, F. M., Fontanier, V., & Procyk, E. (2016) · Nature Communications · doi:10.1038/ncomms11990 · Cited by 83 · see citing works
Asking the right questions about the psychology of human inquiry: Nine open challenges
Coenen, A., Nelson, J. D., & Gureckis, T. M. (2018) · Psychonomic Bulletin & Review · doi:10.3758/s13423-018-1470-5 · Cited by 84 · see citing works
On educating, curiosity, and interest development
Hidi, S. E., & Renninger, K. A. (2020) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2020.08.002 · Cited by 85 · see citing works
Gaze entropy reflects surgical task load
Stasi, L. L. D., Díaz-Piedra, C., Rieiro, H., Sanchez-Carrion, J. M., Berrido, M. M., Granados, G. O., & Catena, A. (2016) · Surgical Endoscopy · doi:10.1007/s00464-016-4851-8 · Cited by 87 · see citing works
Curious to eat insects? Curiosity as a Key Predictor of Willingness to try novel food
Stone, H., FitzGibbon, L., Millan, E. S., & Murayama, K. (2021) · Appetite · doi:10.1016/j.appet.2021.105790 · Cited by 86 · see citing works
Parietal neurons encode expected gains in instrumental information
Foley, N. C., Kelly, S. P., Mhatre, H., Lopes, M. C., & Gottlieb, J. P. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1613844114 · Cited by 76 · see citing works
Self-citationWhy so curious? Quantifying mechanisms of information seeking
van Lieshout, L. L. F., de Lange, F. P., & Cools, R. (2020) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2020.08.005 · Cited by 79 · see citing works
Dissociating neural learning signals in human sign- and goal-trackers
Schad, D. J., Rapp, M. A., Garbusow, M., Nebe, S., Sebold, M., Obst, E., Sommer, C., Deserno, L., Rabovsky, M., Friedel, E., et al. (2019) · Nature Human Behaviour · doi:10.1038/s41562-019-0765-5 · Cited by 81 · see citing works
Panitz, C., Endres, D. M., Buchholz, M., Khosrowtaj, Z., Sperl, M. F. J., Mueller, E., Schubö, A., Schütz, A. C., Teige-Mocigemba, S., & Pinquart, M. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.726432 · Cited by 73 · see citing works
Monkeys are curious about counterfactual outcomes
Wang, M. Z., & Hayden, B. Y. (2019) · Cognition · doi:10.1016/j.cognition.2019.03.009 · Cited by 76 · see citing works
A curious formulation robot enables the discovery of a novel protocell behavior
Grizou, J., Points, L. J., Sharma, A., & Cronin, L. (2020) · Science Advances · doi:10.1126/sciadv.aay4237 · Cited by 77 · see citing works
What Is Consciousness, and Could Machines Have It?
Dehaene, S., Lau, H. C., & Kouider, S. (2021) · Springer eBooks · doi:10.1007/978-3-030-54173-6_4 · Cited by 76 · see citing works
Interest: A unique affective and cognitive motivational variable that develops
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The Posterior Parietal Cortex in Adaptive Visual Processing
Yaoda Xu, A. (2018) · Trends in Neurosciences · doi:10.1016/j.tins.2018.07.012 · Cited by 72 · see citing works
“Perhaps for this reason, and because of our curiosity to continuously seek new information from the environment [92], it is advantageous and adaptive for the PPC to encode salient external visual events”
Intrinsically regulated learning is modulated by synaptic dopamine signaling
Ripollés, P., Ferreri, L., Herrero, E. M., Alicart, H., Gómez-Andrés, A., Marco‐Pallarés, J., Antonijoan, R. M., Noesselt, T., Valle, M., Jordi Riba, A., et al. (2018) · eLife · doi:10.7554/elife.38113 · Cited by 73 · see citing works
Costly curiosity: People pay a price to resolve an uncertain gamble early.
Cabrero, J. A. M. R., Zhu, J.-Q., & Ludvig, E. A. (2018) · Behavioural Processes · doi:10.1016/j.beproc.2018.12.015 · Cited by 63 · see citing works
The Embodied-Enactive-Interactive Brain: Bridging Neuroscience and Creative Arts Therapies
Vaisvaser, S. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.634079 · Cited by 76 · see citing works
Dubourg, E., & Baumard, N. (2021) · Behavioral and Brain Sciences · doi:10.1017/s0140525x21000923 · Cited by 71 · see citing works
Curiosity and the dynamics of optimal exploration
Poli, F., O’Reilly, J. X., Mars, R. B., & Hunnius, S. (2024) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2024.02.001 · Cited by 79 · see citing works
Rule, J., Tenenbaum, J. B., & Piantadosi, S. T. (2020) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2020.07.005 · Cited by 68 · see citing works
On the automaticity of attentional orienting to threatening stimuli.
Anderson, B. A., & Britton, M. K. (2019) · Emotion · doi:10.1037/emo0000596 · Cited by 66 · see citing works
Schillaci, G., Hafner, V. V., & Lara, B. (2016) · Frontiers in Robotics and AI · doi:10.3389/frobt.2016.00039 · Cited by 69 · see citing works
“Information seeking through exploration behaviors, according to Gottlieb et al. (2013), is “a process that obeys the imperative to reduce uncertainty and can be extrinsically or intrinsically motivated.” This is in line with what has been proposed by Litman (2005), as mentioned before in this section, that the drive o…”
InfluentialConscious agent networks: Formal analysis and application to cognition
Fields, C., Hoffman, D. D., Prakash, C., & Singh, M. (2017) · Cognitive Systems Research · doi:10.1016/j.cogsys.2017.10.003 · Cited by 64 · see citing works
“As Gottlieb et al. (2013) emphasize, however, rational agents do not exhibit unlimited curiosity, as this can lead to expending all available resources attempting to solve unsolvable problems or learn unlearnable information.”
Jezzini, A., Bromberg-Martin, E. S., Trambaiolli, L. R., Haber, S. N., & Monosov, I. E. (2021) · Neuron · doi:10.1016/j.neuron.2021.05.013 · Cited by 58 · see citing works
Early Word Segmentation in Naturalistic Environments: Limited Effects of Speech Register
Schreiner, M. S., Altvater‐Mackensen, N., & Mani, N. (2016) · Infancy · doi:10.1111/infa.12133 · Cited by 64 · see citing works
Begus, K., & Southgate, V. (2018) · Springer eBooks · doi:10.1007/978-3-319-77182-3_2 · Cited by 68 · see citing works
Contributions of expected learning progress and perceptual novelty to curiosity-driven exploration
Poli, F., Meyer, M., Mars, R. B., & Hunnius, S. (2022) · Cognition · doi:10.1016/j.cognition.2022.105119 · Cited by 65 · see citing works
The Theoretical and Methodological Opportunities Afforded by Guided Play With Young Children
Yu, Y., Shafto, P., Bonawitz, E., Yang, S. C.-H., Golinkoff, R. M., Corriveau, K. H., Hirsh-Pasek, K., & Xu, F. (2018) · Frontiers in Psychology · doi:10.3389/fpsyg.2018.01152 · Cited by 59 · see citing works
- Authors
- Gottlieb, J., Oudeyer, P.-Y., Lopes, M., & Baranes, A.
- Affiliations
- Columbia University (US)
- Institut national de recherche en sciences et technologies du numérique (FR)
- Corresponding author
- Gottlieb, Jacqueline
- Venue
- Trends in Cognitive Sciences
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 17
- Issue
- 11
- Pages
- 585-593
- ISSN
- 1364-6613 (ISSN-L)
- PMC
- PMC4193662
- OpenAlex
- W2013830186
- Semantic Scholar
- 61667ccec10748b39e274f2a13fcf9b7c4a9b275
- Cited by
- 784
- References
- 132
- Citations by year
- 2026: 43 · 2025: 57 · 2024: 77 · 2023: 165 · 2022: 70 · 2021: 68 · 2020: 64 · 2019: 74 · 2018: 42 · 2017: 43 · 2016: 31 · 2015: 21 · 2014: 26 · 2013: 2
- FWCI
- 4.42
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Trends in Cognitive Sciences (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion)
- Funders
- National Institutes of Health (4r01mh098039-05)
- National Institute of Mental Health (R01 MH-098039, R03MH091590)
- National Institute on Drug Abuse (R21DA030095)
- National Eye Institute (P30EY019007)
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Psychological and Educational Research Studies
- Physical Sciences › Computer Science › Artificial Intelligence › Reinforcement Learning in Robotics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- information seeking, curiosity, attention, exploration, novelty bias, surprise, information gain, eye movements, oculomotor system
- MeSH terms
- Animals, Artificial Intelligence, Attention, Brain, Exploratory Behavior, Humans, Information Seeking Behavior
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
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