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Individual choice behavior: A theoretical analysis.
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“This follows the Bradley-Terry model (Bradley and Terry, 1952) for estimating score functions from pairwise preferences, and is the specialization of the Luce-Shephard choice rule (Luce, 2005; Shepard, 1957) to preferences over trajectory segments.”
From Deep reinforcement learning from human preferences (2017) · cites this paper as Luce, 2005
In the citing paper
“Research into human choice suggests that both explicit and implicit choices systematically vary based on context, especially the other options that are present when choosing [56–59].”
From Evolution and impact of bias in human and machine learning algorithm interaction (2020) · cites this paper as [56]
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Preference Elicitation and Interview Minimization in Stable Matchings
Drummond, J., & Boutilier, C. E. (2014) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v28i1.8829 · Cited by 34
“Having rank-distance determine the difficulty of comparison (or odds of choosing incorrectly) is commonly assumed in econometrics and psychometrics as well (e.g., as in the Luce-Shepard choice model (Luce 1959; Shepard 1959)).”
BackgroundMethodRandom belief equilibrium in normal form games
Friedman, J. W., & Mezzetti, C. (2003) · Games and Economic Behavior · doi:10.1016/j.geb.2003.08.004 · Cited by 34
“We show that this implies that not all trembling hand perfect Nash equilibria are robust and not all robust equilibria are perfect.”
BackgroundIncentives for Energy Conservation in the Commercial and Industrial Sectors
Train, K. E. (1988) · The Energy Journal · doi:10.5547/issn0195-6574-ej-vol9-no3-5 · Cited by 34
An Evolutionary Theory of Economic Interaction: Introduction to Socio- and Econo-Physics
Aruka, Y., & Mimkes, J. (2011) · Physica-Verlag eBooks · doi:10.1007/978-3-7908-2618-0_4 · Cited by 33
“– 146 – 1) The multinomial logit model can be compatible with the sequential choice model, as the Luce model (Luce, 1959) suggested.”
MethodUncovering contrast categories in categorization with a probabilistic threshold model.
Verheyen, S., Deyne, S. D., Dry, M. J., & Storms, G. (2011) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/a0024431 · Cited by 33
“also includes various models that rely on Luce's (1959) choice”
MethodDiverse Randomized Agents Vote to Win
Jiang, A. X., Marcolino, L. S., Procaccia, A. D., Sandholm, T., Shah, N., & Tambe, M. (2018) · Figshare · doi:10.1184/r1/6604934 · Cited by 33
Machine learning of consistent thermodynamic models using automatic differentiation
Rosenberger, D., Barros, K. M., Germann, T. C., & Lubbers, N. (2022) · Physical review. E · doi:10.1103/physreve.105.045301 · Cited by 32
“Each neuron is activated with the Softmax function [24, 25].”
BackgroundKumar, D., Hoyle, C. J., Chen, W., et al. (2009) · International Journal of Product Development · doi:10.1504/ijpd.2009.024199 · Cited by 33
Shen, G., & Wang, J. (2012) · Journal of Transportation Technologies · doi:10.4236/jtts.2012.22019 · Cited by 33
“[10] was the first to use the multinomial logit model in theoretical analysis of individual choice behavior and provided a key component to the multinomial logit with the influential independence of irrelevant alternatives (IIA).”
BackgroundMethodVecchiato, D. (2014) · Aestimum · doi:10.13128/aestimum-14707 · Cited by 33
“In fact CE is based on Random Utility Models (RUMs) (Luce, 1959; Manski, 1977; McFadden, 1974; Thurstone, 1927; Yellott, 1977), which assume that utility is derived from the properties/ characteristics of goods/services rather than directly from the goods themselves.”
Yıldız, K. (2016) · Theoretical Economics · doi:10.3982/te1298 · Cited by 33
“(2010), Tyson (2008), and Manzini et al. (2013). 7That is, an alternative x is chosen when compared to another alternative y , and y is chosen when compared to a third alternative z, but z is chosen when compared to x. For experimental findings, see Tversky (1969), Loomes et al.”
BackgroundMethodCognitive Choice Processes and the Attitude-Behavior Relation
Albert, D., Aschenbrenner, K. M., & Schmalhofer, F. (1989) · Springer eBooks · doi:10.1007/978-1-4612-3504-0_3 · Cited by 33
Effects of the Advisor and Environment on Requesting and Complying With Automated Advice
Sutherland, S. C., Harteveld, C., & Young, M. E. (2016) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/2905370 · Cited by 35
“However, we will highlight this as a potential limitation in Section 5, as it is not possible to determine whether any effect on performance was present.”
BackgroundThree strategies to success: Learning adversary models in security games
Haghtalab, N., Fang, F., Nguyen, T. H., et al. (2016) · Singapore Management University Institutional Knowledge (InK) (Singapore Management University) · Cited by 32
Rational inattention and tonic dopamine
Mikhael, J. G., Lai, L., & Gershman, S. J. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008659 · Cited by 34
“Standard models of action selection posit that the probability of selecting action Ai with estimated value μ̂i 665 follows a softmax function [105, 106]: 666 p(Ai) = ei ∑ j e βμ̂j , (15) where β is referred to as the inverse temperature parameter.”
BackgroundMethodMODELLING COGNITIVELY BOUNDED RATIONALITY: AN EVALUATIVE TAXONOMY
Mallard, G. (2011) · Journal of Economic Surveys · doi:10.1111/j.1467-6419.2010.00673.x · Cited by 31
Collective Irrationality and Positive Feedback
Nicolis, S. C., Zabzina, N., Latty, T. M., & Sumpter, D. J. T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018901 · Cited by 30
“alters the value of the two superior options, and can thus be classified as ‘irrational’ [5].”
BackgroundChambers, C. P., & Hayashi, T. (2012) · Journal of Economic Theory · doi:10.1016/j.jet.2012.01.013 · Cited by 41
“Under the Luce condition, we have p(x|B) = p(x|X)∑ z∈B p(x”
BackgroundInfluentialAlgorithm selection in bilateral negotiation
Ilany, L., & Gal, K. (2015) · Autonomous Agents and Multi-Agent Systems · doi:10.1007/s10458-015-9302-8 · Cited by 32
“Most notably the epsilon-greedy strategy consists of choosing a random lever with epsilon-frequency, and otherwise choosing the lever with the highest estimated mean [51], and the soft-max strategy [52] which an arm is sampled according to a distribution that is an estimate of its performance (we refer the reader to t…”
BackgroundFriend or foe? Social ties in bribery and corruption
Zheng, J. D., Schram, A. J. H. C., & Doğan, G. (2020) · Experimental Economics · doi:10.1007/s10683-020-09683-7 · Cited by 31
“Assuming that follows a type-I extreme value distribution (Luce 2005) this yields the probability that performer j is preferred by evaluator i”
Online game QoE evaluation using paired comparisons
Chang, Y., Chen, K.-T., Wu, C., et al. (2010) · IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR) · doi:10.1109/cqr.2010.5619923 · Cited by 31
“One of the most widely used models for this purpose is the Bradley-Terry-Luce (BTL) model [8, 20], which predicts Pij , the probability of choosing Ti over Tj , as a function associated with the true ratings of the two stimuli:”
MethodMonotonicity of ?ranking by choosing?: A progress report
Bouyssou, D. (2004) · Social Choice and Welfare · doi:10.1007/s00355-003-0250-x · Cited by 31
“…(1953) and Debord (1987b), – Multiple criteria decision making using “ordinal information” (see Arrow and Raynaud, 1986; Roy, 1991), in view of the results in Bouyssou (1996), – Psychology with, e.g., the study of binary choice probabilities (see Luce, 1959; Suppes, Krantz, Luce and Tversky, 1989).”
BackgroundPhonotactics as phonology: knowledge of a complex restriction in Dutch
Kager, R., & Pater, J. (2012) · Phonology · doi:10.1017/s0952675712000048 · Cited by 31
Gureckis, T. M., & Love, B. C. (2010) · Cognitive Science · doi:10.1111/j.1551-6709.2009.01076.x · Cited by 33
“LASR’s buffer-based memory addresses one of the early criticisms of models based on associative chains. In LASR, repeated elements of the same type are represented separately with a distinct trace (i.e., repeated elements are given separate memory slots). As a result, LASR has no difficulty learning a simple sequence…”
BackgroundThe effect of predictive history on the learning of sub-sequence contingencies
Beesley, T., & Pelley, M. E. L. (2009) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470210902831767 · Cited by 31
“The accuracy of the model in selecting the next element was calculated as the activation of the target output unit divided by the total activation of all output units, commonly referred to as the Luce choice ratio (hereafter LCR; Luce, 1959).”
MethodBinaural "loudness" summation: Probabilistic theory and data.
Falmagne, J., Iverson, G., & Marcovici, S. (1979) · Psychological Review · doi:10.1037//0033-295x.86.1.25 · Cited by 31
Choice and habituation as measures of response similarity.
Jacobson, E., & Premack, D. (1970) · Journal of Experimental Psychology · doi:10.1037/h0029560 · Cited by 31
Better-than-Demonstrator Imitation Learning via Automatically-Ranked DemonstrationsPreprint
Brown, D. S., Goo, W., & Niekum, S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.03976 · Cited by 70
“The reward function R̂θ is trained using a pair-wise ranking loss [38] based on the Luce-Shephard choice rule [39]:”
MethodLearning from Suboptimal Demonstration via Self-Supervised Reward RegressionPreprint
Chen, L., Paleja, R., & Gombolay, M. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.11723 · Cited by 49
“Finally, D-REX learns via Equation 3 the reward function through supervised learning on the trajectories’ rankings, using a pairwise ranking loss according to Luce-Shepard rule [20].”
MethodDevaine, M., & Jean Daunizeau, A. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005422 · Cited by 32
Rice, C. A., Beekhuizen, B., Dubrovsky, V., et al. (2018) · Behavior Research Methods · doi:10.3758/s13428-018-1107-7 · Cited by 30
“Extensive theoretical, computational, and empirical evidence has documented clear non-linearities in how representations of the actual probability distributions used as evidence to generate a response map onto the generated response (Luce, 2005; Tversky, 1967; Ungemach, Chater, & Stewart, 2009).”
BackgroundA Computational Account of the Development of the Generalization of Shape Information
Doumas, L. A. A., & Hummel, J. E. (2010) · Cognitive Science · doi:10.1111/j.1551-6709.2010.01103.x · Cited by 30
“…Retrieval consists of activating the representation of the test exemplar and allowing it to pass activation, via the semantic units, to the representations in LTM and using the Luce (1959) choice axiom to retrieve these active LTM representations into working memory (WM) (see Doumas et al., 2008).”
MethodThe best of times and the worst of times are interchangeable.
Hawkins, G. E., Marley, A. A. J., Heathcote, A., Flynn, T. N., Louviere, J. J., & Brown, S. D. (2014) · Decision · doi:10.1037/dec0000012 · Cited by 27
“When only choices are modeled, and with certain restrictions on its parameters, the LBA is a random utility model, similar to the multinomial logit (Luce choice) model (Luce, 1959; Marley & Flynn, in press).”
MethodEquilibria in multi-party competition under uncertainty
de Palma, A., Hong, G.-S., & Thisse, J. (1990) · Social Choice and Welfare · doi:10.1007/bf01395725 · Cited by 30
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from ObservationsPreprint
Brown, D. S., Goo, W., Nagarajan, P., & Niekum, S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.06387 · Cited by 171
“This form of loss function follows from the classic Bradley-Terry and Luce-Shephard models of preferences (Bradley & Terry, 1952; Luce, 2012) and has been shown to be effective for training neural networks from preferences (Christiano et al., 2017; Ibarz et al., 2018).”
MethodPerceived similarity of exact and inexact transpositions
van Egmond, R., & Povel, D.-J. (1996) · Acta Psychologica · doi:10.1016/0001-6918(95)00043-7 · Cited by 29
“of the BTL-model (Bradley and Terry, 1952; Luce, 1959 ), yielding scale values for each type of transposition.”
MethodGoodman, N. D., Frank, M. C., Griffiths, T. L., Tenenbaum, J. B., Battaglia, P., & Hamrick, J. B. (2015) · Psychological Science · doi:10.1177/0956797614559544 · Cited by 29
“The soft-max rule is foundational in economics, decision theory, and cognitive psychology (Luce, 1959, 1977), and we first selected it for this problem on the basis of a completely independent set of experiments (Frank, Goodman, Lai, & Tenenbaum, 2009).”
The unavailable candidate model
Lu, T., & Boutilier, C. E. (2010) · ACM Conference on Electronic Commerce (EC) · doi:10.1145/1807342.1807385 · Cited by 29
Active Learning of Reward Dynamics from Hierarchical Queries
Basu, C., Bıyık, E., He, Z., Singhal, M., & Sadigh, D. (2019) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros40897.2019.8968522 · Cited by 28
“Then, the user response to a sub-query qi is probabilistic based on Luce’s Choice Axiom [38], [39] which is a widely used human decision model in cognitive science as it nicely captures the uncertainty in humans’ choices: P (ai|qi,mi, w) = exp(Rmi(q ai i )) exp(Rmi(q ai i )) + exp(Rmi(q āi i )) (2) This models probab…”
MethodImpacts of Game-Theoretic Activation on Epidemic Spread over Dynamical Networks
Hota, A. R., Sneh, T., & Gupta, K. (2021) · SIAM Journal on Control and Optimization · doi:10.1137/20m1376923 · Cited by 29
“We assume that nodes choose their actions according to the logit choice model which captures bounded rationality prevalent in human decision-making [35, 36], and consider the notion of quantal response equilibrium (QRE) [37] as the solution concept.”
MethodImpact of Heterogeneity and Risk Aversion on Task Allocation in Multi-Agent Teams
Wu, H., Ghadami, A., Bayrak, A. E., et al. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3097259 · Cited by 29
“To model noise in agent decisions, we incorporate a noisy rational model, a widely used human decision model in cognitive science [19]–[21], into our proposed framework.”
MethodSeeking positive experiences can produce illusory correlations
Denrell, J. C., & Mens, G. L. (2011) · Cognition · doi:10.1016/j.cognition.2011.01.007 · Cited by 29
“The logistic choice rule has often been used to model choices under uncertainty (e.g. Luce, 1959).”
An Integrated Latent Variable Choice Modeling Approach for Enhancing Product Demand Modeling
Wassenaar, H. J., Chen, W., Cheng, J., et al. (2004) · doi:10.1115/detc2004-57487 · Cited by 29
A Study of Driver’s Route Choice Behavior Based on Evolutionary Game Theory
Jiang, X., Ji, Y., Du, M., & Deng, W. (2014) · Computational Intelligence and Neuroscience · doi:10.1155/2014/124716 · Cited by 32
“The aim of this work is to propose such an analytic method that is able to take traffic information into account to explore the mechanism of route choice behavior.”
Veríssimo, J., & Clahsen, H. (2014) · Journal of Memory and Language · doi:10.1016/j.jml.2014.06.001 · Cited by 28
The model of hierarchical complexity as a measurement system.
Commons, M. L., Gane-McCalla, R., Barker, C. D., et al. (2014) · Behavioral Development · doi:10.1037/h0100583 · Cited by 29
Pragmatic Back-and-Forth Reasoning
Franke, M., & Jäger, G. (2014) · Palgrave Macmillan UK eBooks · doi:10.1057/9781137333285_7 · Cited by 29
Interactive Social Recommendation
Wang, X. Y., Hoi, S. C. H., Liu, C., & Ester, M. (2017) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3132847.3132880 · Cited by 29
“Softmax methods are based on Luce’s axiom of choice [57] and pick each item for recommendation with a probability that is proportional to its average reward.”
MethodDesigning social choice mechanisms using machine learning
Xia, L. (2013) · doi:10.5555/2484920.2484995 · Cited by 29
Testing the interval-level measurement property of multi-item visual analogue scales
Krabbe, P., Stalmeier, P., Lamers, L., & Busschbach, J. (2006) · Quality of Life Research · doi:10.1007/s11136-006-0027-7 · Cited by 39
“Drawing on Thurstone’s work, Luce [13] formulated models of discrete probabilistic choice, i.e., random utility models.”
MethodUnite and Conquer: A Multiplicative Inequality for Choice Probabilities
Sattath, S., & Tversky, A. (1976) · Econometrica · doi:10.2307/1911382 · Cited by 29
Inequalities for Random Utility Models, with Applications to Ranking and Subset Choice Data
Joe, H. (2000) · Methodology And Computing In Applied Probability · doi:10.1023/a:1010058117460 · Cited by 28
Smart mobility – an analysis of potential customers’ preference structures
Schulz, T., Böhm, M., Gewald, H., et al. (2020) · Electronic Markets · doi:10.1007/s12525-020-00446-z · Cited by 28
“Important contributions to the discrete choice analysis have been made by, among others, Luce (2005) and McFadden (1980).”
BackgroundYuan, Y., & Yabe, M. (2014) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph120100176 · Cited by 28
“The CE method has its theoretical grounding in Lancaster’s model of consumer choice [33] and its econometric basis in random utility theory [34,35].”
MethodJoo, S., Lee, P., & Stark, S. E. (2019) · Behavior Research Methods · doi:10.3758/s13428-019-01274-6 · Cited by 28
Balderjahn, I., Hedergott, D., & Peyer, M. (2009) · Springer eBooks · doi:10.1007/978-3-642-00754-5_9 · Cited by 28
The nature of phoneme representation in spoken word recognition.
Gaskell, M. G., Quinlan, P. T., Tamminen, J., & Cleland, A. A. (2008) · Journal of Experimental Psychology General · doi:10.1037/0096-3445.137.2.282 · Cited by 28
An integrated utility-based model of conflict evaluation and resolution in the Stroop task.
Chuderski, A., & Smoleń, T. (2016) · Psychological Review · doi:10.1037/a0039979 · Cited by 28
“The choice of rule Z depends on the stochastic procedure based on the nonlinear Luce (1959) ratio: Pi eU i n j eU j n (5) where Pi denotes the probability that rule i will be selected, and j reflects all rules within response set .”
MethodRanked Additive Utility Representations of Gambles: Old and New Axiomatizations
Luce, R. D., & Marley, A. A. J. (2005) · Journal of Risk and Uncertainty · doi:10.1007/s11166-005-5832-9 · Cited by 29
“Most theories of utility, including the RWU one described in Marley and Luce (2001), have either explicitly or implicitly assumed idempotence. Luce and Marley (2000) present some theoretical results for non-idempotent binary gambles. To our knowledge, no related theoretical work has been done on failures of idempotenc…”
BackgroundInfluentialSelf-citationFinite integer models for learning in individual subjects.
Theios, J. (1968) · Psychological Review · doi:10.1037/h0025889 · Cited by 28
Consumer Resource Allocation Models at the Individual Level
Batsell, R. R. (1980) · Journal of Consumer Research · doi:10.1086/208795 · Cited by 28
Shallow, C., Iliev, R. I., & Medin, D. L. (2011) · Judgment and Decision Making · doi:10.1017/s1930297500002631 · Cited by 26
“moral dilemmas to broader contexts shows parallels with the development of choice theory (Luce, 1959).”
BackgroundMajumder, A., & Shrivastava, N. (2013) · International World Wide Web Conference (WWW) · doi:10.1145/2488388.2488464 · Cited by 26
“Score based models [12], on the other hand, are very efficient as they divide permutation construction into stages and assign scores on each stage such that the final probability is a combination (multiplication) of stage-wise scores.”
BackgroundModeling the demand for outdoor recreation
Mendelsohn, R. O. (1987) · Water Resources Research · doi:10.1029/wr023i005p00961 · Cited by 27
Learning and memory for personality prototypes.
Mayer, J. D., & Bower, G. H. (1986) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.51.3.473 · Cited by 27
The softmax function: Properties, motivation, and interpretationPreprint
Franke, M., & Degen, J. (2023) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/vsw47 · Cited by 36
Strategies of Persuasion, Manipulation and Propaganda: Psychological and Social Aspects
Franke, M., & van Rooij, R. (2015) · Lecture notes in computer science · doi:10.1007/978-3-662-48540-8_8 · Cited by 29
“Still, already May [53] has shown that cyclic preferences were not extraordinary (violating transitivity of the preference relation), and Luce [51] noted that people sometimes seem to choose one alternative over another with a given consistent probability not equal to one (violating completeness of the preference rela…”
BackgroundRestricted Boltzmann machines modeling human choice
Osogami, T., & Otsuka, M. (2014) · neural information processing systems · Cited by 26
Neural Utterance Ranking Model for Conversational Dialogue Systems
Inaba, M., & Takahashi, K. (2016) · Annual Meeting of the Special Interest Group on Discourse and Dialogue · doi:10.18653/v1/w16-3648 · Cited by 25
“Several methods for modeling rank data have been proposed, including the Bradley-Terry-Luce model (Bradley and Terry, 1952; Luce, 1959), the Mallows model (Mallows, 1957) and the Plackett-Luce model (Plackett, 1975; Luce, 1959).”
MethodScaled Autonomy: Enabling Human Operators to Control Robot Fleets
Swamy, G., Reddy, S., Levine, S., & Dragan, A. D. (2020) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra40945.2020.9196792 · Cited by 28
“note f1;2;:::;ng, i2[n] denote the i-th robot in a fleet of n robots, and it H 2[n] denote the robot controlled by the user at time t. We assume the user selects robot it H using the Luce choice model [12], P[ it H =]= e f(s t i ) n å j=1 f(s j ); (1) where f : S !R is the user’s scoring function, and st i is the state…”
MethodContests with the Probability of a Draw: A Stochastic Foundation*
Jia, H. (2012) · Economic Record · doi:10.1111/j.1475-4932.2012.00822.x · Cited by 26
Learning to rank by aggregating expert preferences
Volkovs, M., Larochelle, H., & Zemel, R. S. (2012) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/2396761.2396868 · Cited by 27
“The Bradley-Terry model was later generalized by Plackett and Luce to a model for permutations [23, 27].”
MethodInvariance of conditional maximum utility
de Palma, A., & Kilani, K. (2005) · Journal of Economic Theory · doi:10.1016/j.jet.2005.05.010 · Cited by 26
Choice, preference, and utility: probabilistic and deterministic representations
Marley, A. A. J. (1920) · Cambridge University Press eBooks · doi:10.1017/9781139245913.008 · Cited by 26
“A major exception is the extensive series of papers on the utility of gambling that develops representations involving a relatively standard idempotent representation, plus a weighted entropy-type term; these results are summarized in Luce et al. (2009).”
BackgroundMethodInfluentialThe Green Choice: Learning and Influencing Human Decisions on Shared Roads
Bıyık, E., Lazar, D. A., Sadigh, D., & Pedarsani, R. (2019) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc40024.2019.9030169 · Cited by 28
“Rather, we draw from Luce’s Choice Axiom [7] to model the probability with which users choose each option, in combination with a softmax rule [26], formalized as follows.”
MethodClassification and comparison via neural networks
Potter, İ. Y., Tian, P., Dy, J., Deniz Erdogmus, B., Brown, J. M., Kalpathy–Cramer, J., Ostmo, S. R., Campbell, J. P., Chiang, M. F., & Ioannidis, S. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.06.004 · Cited by 24
“Given a top-1 ranking dataset, the total order of N items can be learned through the Plackett-Luce (PL) model (Luce, 2012).”
MethodOn desire, aversion, and the affective zero.
Irwin, F. W. (1961) · Psychological Review · doi:10.1037/h0038868 · Cited by 26
Physics and Financial Economics (1776-2014): Puzzles, Ising and Agent-Based ModelsPreprint
Sornette, D. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2421155 · Cited by 26
Phantom alternatives influence food preferences in the eastern honeybee A pis cerana
Tan, K., Dong, S., Liu, X., et al. (2014) · Journal of Animal Ecology · doi:10.1111/1365-2656.12288 · Cited by 25
“Most models of animal and human multi-attribute choice make the implicit assumption that an individual’s preference for a particular item does not change when irrelevant items are added to the choice set (Luce 1959; Rapoport 1989).”
BackgroundA Royal Road to Consequentialism?
Peterson, M. (2009) · Ethical Theory and Moral Practice · doi:10.1007/s10677-009-9198-y · Cited by 25
“The choice axiom implies the existence of a cardinal utility scale. THEOREM 5.1 ( Luce 1959 /2005).”
BackgroundInfluentialSeymour, B., Barbe, M. T., Dayan, P., Shiner, T., Dolan, R. J., & Fink, G. R. (2016) · Scientific Reports · doi:10.1038/srep32509 · Cited by 31
Healthcare consumers' opt-in intentions to Health Information Exchanges (HIEs): An empirical study
Esmaeilzadeh, P. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.02.029 · Cited by 26
Microscopic modelling of area-based heterogeneous traffic flow: Area selection and vehicle movement
Sarkar, N. C., Bhaskar, A., Zheng, Z., et al. (2020) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2019.12.013 · Cited by 25
“Interested readers should refer to Luce (2005) for a detailed description of a logit model and Hensher, Rose, and Greene (2005) for a details of a probit model.”
BackgroundQuantification of Health States with Rank-Based Nonmetric Multidimensional Scaling
Krabbe, P., Salomon, J., & Murray, C. (2007) · Medical decision making · doi:10.1177/0272989x07302131 · Cited by 31
A stochastic rank ordered logit model for rating multi-competitor games and sports
Glickman, M. E., & Hennessy, J. (2015) · Journal of Quantitative Analysis in Sports · doi:10.1515/jqas-2015-0012 · Cited by 26
“The rank ordering model based on extreme value distributions is sometimes called the Plackett-Luce model, as an extension of the multinomial logit choice model of Luce (1959) to rank orderings.”
BackgroundMethodJoo, S., Lee, P., & Stark, S. E. (2018) · Journal of Educational Measurement · doi:10.1111/jedm.12183 · Cited by 25
Individualized rank aggregation using nuclear norm regularization
Lu, Y., & Negahban, S. N. (2015) · Allerton Conference on Communication, Control, and Computing · doi:10.1109/allerton.2015.7447183 · Cited by 25
“Given how natural the problem of rank aggregation is, there has been a wide body recent [1], [2] and classical work [3]–[6] to understand how to consistently combine preferences.”
BackgroundIto, K., Okamoto, S., Yamada, Y., & Kajimoto, H. (2019) · ACM Transactions on Applied Perception · doi:10.1145/3340961 · Cited by 24
“Hence, we adopted anm-alternative forced-choice task [10, 33, 36, 53] that is an expansion of the two-alternative forced-choice task.”
MethodBaumann, J. H., Fischer, M. M., & Schubert, U. (1983) · Papers of the Regional Science Association · doi:10.1111/j.1435-5597.1983.tb01651.x · Cited by 25
Depression genetic risk score is associated with anhedonia-related markers across units of analysis
Guffanti, G., Kumar, P., Admon, R., Treadway, M. T., Hall, M., Mehta, M., Douglas, S., Arulpragasam, A. R., & Pizzagalli, D. A. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0566-7 · Cited by 26
Tracking the decoy: maximizing the decoy effect through sequential experimentation
Kaptein, M. C., van Emden, R., & Iannuzzi, D. (2016) · Humanities and Social Sciences Communications · doi:10.1057/palcomms.2016.82 · Cited by 24
“This decoy (or “asymmetric dominance”) effect clearly violates the “axiom of regularity” of rational choice theory: when given a choice set A, where A⊂B, the probability of choosing an element x from B cannot be greater than the probability of choosing x from A (Luce, 1959; Yang, 2013).”
BackgroundCohen, D., Teichman, G., Volovich, M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11715-7 · Cited by 24
Yingzhi, Lin, L., Xiangzheng, et al. (2014) · 地球科学前沿:英文版 · Cited by 24
Modeling gain-loss asymmetries in risky choice : The critical role of probability weighting
Pachur, T., & Kellen, D. (2013) · eScholarship (California Digital Library) · Cited by 24
Consumer choice behaviour and new product development: an integrated market simulation approach
Tsafarakis, S., Grigoroudis, E., & Matsatsinis, N. F. (2010) · Journal of the Operational Research Society · doi:10.1057/jors.2010.70 · Cited by 24
“Popular choice models usually applied in market simulations are the BTL (Bradley and Terry, 1952), a constant utility model which uses a probabilistic choice rule (Luce, 1959), and the MNL (McFadden, 1974), a random utility model with a deterministic choice rule (Baltas et al, 1997).”
The impact of marketing policy on promotional price elasticities and baseline sales
Zenor, M. J., Bronnenberg, B. J., & McAlister, L. M. (1998) · Journal of Retailing and Consumer Services · doi:10.1016/s0969-6989(97)00001-5 · Cited by 24
“We represent preferences for Bl and B2 by it and (l-7t) respectively (0<7t<l); and assume that, in the absence of promotion, consumers choose between brands with probabilities proportional to preferences (Luce, 1959).”
BackgroundRational decisions: The adaptive nature of context-dependent choice
Rosati, A. G., & Stevens, J. R. (2009) · Lincoln (University of Nebraska) · Cited by 25
Hidden actions and preferences for timing of resolution of uncertainty
Ergin, H. I., & Sarver, T. (2015) · Theoretical Economics · doi:10.3982/te1340 · Cited by 24
Webb, R., Glimcher, P. W., & Louie, K. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2462895 · Cited by 24
Subcortical connectivity correlates selectively with attention’s effects on spatial choice bias
Sreenivasan, V., & Sridharan, D. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1902704116 · Cited by 24
Metadata
- Authors
- Luce, R. D.
- Affiliations
- University of California, Irvine (US)
- Corresponding author
- Luce, R. Duncan
- Venue
- Dover Publications eBooks
- Publisher
- Dover Publications
- Published
- 2005
- OpenAlex
- W2094536313
- Cited by
- 1,157
- References
- 0
- Citations by year
- 2026: 5 · 2025: 14 · 2024: 18 · 2023: 36 · 2022: 27 · 2021: 55 · 2020: 43 · 2019: 51 · 2018: 45 · 2017: 35 · 2016: 48 · 2015: 81 · 2014: 74 · 2013: 68 · 2012: 53
- FWCI
- 20.89
- Type
- book
- Language
- en
- Open access
- closed
- Locations
- Dover Publications eBooks (publishedVersion)
- Funders
- National Science Foundation (NSF-G2803)
- Office of Naval Research (G-4506)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Economic Theory and Institutions
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Experimental Behavioral Economics Studies
- Keywords
- decision-making, choice theory, consumer behavior, utility maximization
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