Cited by 362Neural and Behavioral Psychology StudiesEmbodied and Extended CognitionMotor Control and Adaptation

The DOI matches its Crossref record; 100 of the 104 references it cites were found in a registry or an index.

The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior.

Gray, Wayne D., Sims, Chris R., Fu, Wai-Tat, Schoelles, Michael J.·2006·Psychological Review

Open this paper in CoChat — free account

Abstract

Soft constraints hypothesis (SCH) is a rational analysis approach that holds that the mixture of perceptual-motor and cognitive resources allocated for interactive behavior is adjusted based on temporal cost-benefit tradeoffs. Alternative approaches maintain that cognitive resources are in some sense protected or conserved in that greater amounts of perceptual-motor effort will be expended to conserve lesser amounts of cognitive effort. One alternative, the minimum memory hypothesis (MMH), holds that people favor strategies that minimize the use of memory. SCH is compared with MMH across 3 experiments and with predictions of an Ideal Performer Model that uses ACT-R's memory system in a reinforcement learning approach that maximizes expected utility by minimizing time. Model and data support the SCH view of resource allocation; at the under 1000-ms level of analysis, mixtures of cognitive and perceptual-motor resources are adjusted based on their cost-benefit tradeoffs for interactive behavior.

Integrity signals

Registry

Crossref · 10.1037/0033-295x.113.3.461

Cites

100 of 100 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1956) · Psychological Review · doi:10.1037/h0043158 · Cited by 17,812
The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1994) · Psychological Review · doi:10.1037/0033-295x.101.2.343 · Cited by 17,559
Technical Note: Q-Learning
Watkins, C., & Dayan, P. (1992) · Machine-mediated learning · doi:10.1023/a:1022676722315 · Cited by 14,277
Q-learning
Watkins, C. J. C. H., & Dayan, P. (1992) · Machine Learning · doi:10.1007/bf00992698 · Cited by 9,083
The Design of Everyday Things
Norman, D. A. (2016) · Vahlen eBooks · doi:10.15358/9783800648108 · Cited by 6,415
Detection Theory: A User's Guide
Macmillan, N. A., & Creelman, C. D. (1991) · Cited by 5,415
Six views of embodied cognition
Wilson, M. (2002) · Psychonomic Bulletin & Review · doi:10.3758/bf03196322 · Cited by 4,782
Unified theories of cognition
(1991) · Choice Reviews Online · doi:10.5860/choice.28-5376 · Cited by 4,218
A capacity theory of comprehension: individual differences in working memory
Just, M. A., & Carpenter, P. A. (1992) · Psychological Review · doi:10.1037/0033-295x.99.1.122 · Cited by 4,153
The Psychology of Human-Computer Interaction
Card, S. K., Moran, T. P., & Newell, A. (2018) · CRC Press eBooks · doi:10.1201/9780203736166 · Cited by 4,103

Flagged first, then by citations

Show all 104 references

4 of the 104 references couldn’t be matched to a known paper.

Research works printed but not linked: 10

Carlson, 2000, Cognitive control of multiplestep routines: Information processing and conscious intentions., 443
10.1037/1076-898X.6.4.322 · DOI
10.1016/j.cogsci.2003.12.001 · DOI · Paper page
10.1016/0364-0213(94)90007-8 · DOI · Paper page
10.1016/S0364-0213(87)80026-5 · DOI
10.1511/2002.3.236 · DOI
Ritter. Using a simulated user to explore human-robot interfaces. IEEE Transactions on System, Man and Cybernetics
Simon, 1996, The sciences of the artificial
10.1037/0278-7393.24.4.1052 · DOI
Todd, (in press). Disintegrated architectures of cognition: The adaptive toolbox for decision making.

Sorted by citations

Items 101–200 of 362

Understanding the cognitive miser: Cue-utilization in effort-based decision making
Dunn, T. L., & Risko, E. F. (2019) · Acta Psychologica · doi:10.1016/j.actpsy.2019.102863 · Cited by 26
Process Systems Engineering and the Human-in-The-Loop: The Smart Control Room
Ghosh, S., & Bequette, B. W. (2019) · Industrial & Engineering Chemistry Research · doi:10.1021/acs.iecr.9b04739 · Cited by 20
Improving the effectiveness of an interruption lag by inducing a memory-based strategy
Morgan, P. L., Patrick, J., & Tiley, L. (2012) · Acta Psychologica · doi:10.1016/j.actpsy.2012.09.003 · Cited by 23
Avoiding the problem state bottleneck by strategic use of the environment
Borst, J. P., Buwalda, T. A., van Rijn, H., & Taatgen, N. A. (2013) · Acta Psychologica · doi:10.1016/j.actpsy.2013.07.016 · Cited by 19
Combining the strengths of naturalistic and laboratory decision-making research to create integrative theories of choice.
Markman, A. B. (2017) · Journal of Applied Research in Memory and Cognition · doi:10.1016/j.jarmac.2017.11.005 · Cited by 20
Framing cognitive offloading in terms of gains or losses: achieving a more optimal use of reminders
Fröscher, L., Friedrich, A.-K., Berentelg, M., Widmer, C. K., Gilbert, S. J., & Papenmeier, F. (2022) · Cognitive Research Principles and Implications · doi:10.1186/s41235-022-00416-3 · Cited by 23
Adaptive Allocation of Vision under Competing Task Demands
Sims, C. R., Jacobs, R. A., & Knill, D. C. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.4240-10.2011 · Cited by 20
Self-citation
Dividing Attention Between Tasks: Testing Whether Explicit Payoff Functions Elicit Optimal Dual‐Task Performance
Farmer, G., Janssen, C. P., Nguyen, A. T., & Brumby, D. P. (2017) · Cognitive Science · doi:10.1111/cogs.12513 · Cited by 20
Strategies for Selecting Routes through Real-World Environments: Relative Topography, Initial Route Straightness, and Cardinal Direction
Brunyé, T. T., Collier, Z. A., Cantelon, J. A., Holmes, A., Wood, M. D., Linkov, I., & Taylor, H. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0124404 · Cited by 20
The influence of training and experience on memory strategy
Patrick, J., Morgan, P. L., Smy, V., Tiley, L., Seeby, H., Patrick, T., & Evans, J. (2015) · Memory & Cognition · doi:10.3758/s13421-014-0501-3 · Cited by 19
Thinking Takes Time: Children Use Agents’ Response Times to Infer the Source, Quality, and Complexity of Their Knowledge
Richardson, E., & Keil, F. C. (2021) · Cognition · doi:10.1016/j.cognition.2022.105073 · Cited by 18
Paying the price works: Increasing goal-state access cost improves problem solving and mitigates the effect of interruption
Morgan, P. L., & Patrick, J. (2012) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2012.702117 · Cited by 19
Framework for Studying Emerging Policy Issues Associated with PHEVs in Managing Coupled Power and Transportation Systems
Kezunović, M., Waller, S. T., & Damnjanovic, I. D. (2010) · IEEE Green Technologies Conference (GreenTech) · doi:10.1109/green.2010.5453787 · Cited by 18
Repeated Web Page Visits and the Scanpath Theory: A Recurrent Pattern Detection Approach
Burmester, M., & Mast, M. (2010) · Journal of Eye Movement Research · doi:10.16910/jemr.3.4.5 · Cited by 18
Adaptive but non-optimal visual search behavior with highlighted displays
Tamborello, F. P., & Byrne, M. D. (2007) · Cognitive Systems Research · doi:10.1016/j.cogsys.2007.05.003 · Cited by 17
Interrogating Feature Learning Models to Discover Insights Into the Development of Human Expertise in a Real‐Time, Dynamic Decision‐Making Task
Sibert, C., Gray, W. D., & Lindstedt, J. K. (2016) · Topics in Cognitive Science · doi:10.1111/tops.12225 · Cited by 19
Self-citation
Investigating the Post-Training Persistence of Expert Interaction Techniques
Lafreniere, B. J., Gutwin, C. A., & Cockburn, A. (2017) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3119928 · Cited by 17
Loss Aversion and Preferences in Interaction
Quinn, P., & Cockburn, A. (2018) · Human-Computer Interaction · doi:10.1080/07370024.2018.1433040 · Cited by 19
Melioration Dominates Maximization: Stable Suboptimal Performance Despite Global Feedback
Neth, H., Sims, C. R., & Gray, W. D. (2006) · KOPS (University of Konstanz) · Cited by 17
Self-citation
The Human-Computer System: Towards an Operational Model for Problem Solving
Ribarsky, W., & Fisher, B. (2016) · Hawaii International Conference on System Sciences (HICSS) · doi:10.1109/hicss.2016.183 · Cited by 16
Predicting Short‐Term Remembering as Boundedly Optimal Strategy Choice
Howes, A., Duggan, G. B., Kalidindi, K., Tseng, Y., & Lewis, R. L. (2015) · Cognitive Science · doi:10.1111/cogs.12271 · Cited by 17
Control used and control felt: Two sides of the agency coin
Potts, C. A., & Carlson, R. A. (2019) · Attention Perception & Psychophysics · doi:10.3758/s13414-019-01771-y · Cited by 17
A New Hope: Human-Centric Cybersecurity Research Embedded Within Organizations
Morgan, P. L., Asquith, P. M., Bishop, L. M., Raywood-Burke, G., Wedgbury, A., & Jones, K. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-50309-3_14 · Cited by 19
Foraging tempo: Human run patterns in multiple-target search are constrained by the rate of successive responses
Thornton, I. M., Nguyen, T. T. N., & Kristjansson, A. K. (2020) · Quarterly Journal of Experimental Psychology · doi:10.1177/1747021820961640 · Cited by 15
Embodiment and Explanation
Clark, A. (2008) · Elsevier eBooks · doi:10.1016/b978-0-08-046616-3.00003-7 · Cited by 14
Much Ado About Cognition
Clark, A. (2010) · Mind · doi:10.1093/mind/fzr002 · Cited by 15
Use of Complementary Actions Decreases with Expertise
Destefano, M., Lindstedt, J. K., & Gray, W. D. (2011) · eScholarship (California Digital Library) · Cited by 14
Self-citation
High spatial validity is not sufficient to elicit voluntary shifts of attention
Pauszek, J. R., & Gibson, B. S. (2016) · Attention Perception & Psychophysics · doi:10.3758/s13414-016-1097-4 · Cited by 14
Improving Recommender Systems Beyond the AlgorithmPreprint
Schnabel, T., Bennett, P. N., & Joachims, T. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1802.07578 · Cited by 14
Supporting Dynamic Instructional Design Decisions Within a Bounded Rationality
Stefaniak, J. E., Tawfik, A. A., & Sentz, J. (2022) · TechTrends · doi:10.1007/s11528-022-00792-z · Cited by 14
Choosing to interleave
Back, J., Cox, A. L., & Brumby, D. P. (2012) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208289 · Cited by 13
Precrastination and individual differences in working memory capacity
Raghunath, N., Fournier, L. R., & Kogan, C. J. (2020) · Psychological Research · doi:10.1007/s00426-020-01373-6 · Cited by 13
The Predation Game: Does dividing attention affect patterns of human foraging?
Thornton, I. M., Tagu, J., Zdravković, S., & Kristjansson, A. K. (2021) · Cognitive Research Principles and Implications · doi:10.1186/s41235-021-00299-w · Cited by 14
Distributed metacognition: Increased bias and deficits in metacognitive sensitivity when retrieving information from the internet.
Dunn, T. L., Gaspar, C., McLean, D., Koehler, D. J., & Risko, E. F. (2021) · Technology Mind and Behavior · doi:10.1037/tmb0000039 · Cited by 16
How Mobile Touch Devices Foster Cognitive Offloading in the Elderly: The Effects of Input and Feedback
Jin, T., He, J., Wang, W., Wu, Z., & Gu, H. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2148859 · Cited by 13
Transferring control demands across incidental learning tasks – stronger sequence usage in serial reaction task after shortcut option in letter string checking
Gaschler, R., Marewski, J. N., Wenke, D., & Frensch, P. A. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.01388 · Cited by 13
Shaping Feedback Data in Recommender Systems with Interventions Based on Information Foraging Theory
Schnabel, T., Bennett, P. N., & Joachims, T. (2019) · ACM International Conference on Web Search and Data Mining (WSDM) · doi:10.1145/3289600.3290974 · Cited by 13
Effects of Item Difficulty on the Retrieval of Solutions during Cognitive Skill Acquisition: Age Differences
Onyper, S. V., Hoyer, W. J., & Cerella, J. (2008) · Aging Neuropsychology and Cognition · doi:10.1080/13825580701879907 · Cited by 13
Evaluating Effort: Influences of Evaluation Mode on Judgments of Task‐specific Efforts
Dunn, T. L., Koehler, D. J., & Risko, E. F. (2017) · Journal of Behavioral Decision Making · doi:10.1002/bdm.2018 · Cited by 15
Visualization as a stimulus domain for vision science
Rensink, R. A. (2021) · Journal of Vision · doi:10.1167/jov.21.8.3 · Cited by 15
Multifaceted consequences of visual distraction during natural behaviour
Kumle, L., Võ, M. L. ‐., Nobre, A. C., & Draschkow, D. (2024) · Communications Psychology · doi:10.1038/s44271-024-00099-0 · Cited by 12
What Makes a UI Simple? Difficulty and Complexity in Tasks Engaging Visual-Spatial Working Memory
Bakaev, M., & Разумникова, О. М. (2021) · Future Internet · doi:10.3390/fi13010021 · Cited by 12
Effects of Information Access Cost and Accountability on Medical Residents’ Information Retrieval Strategy and Performance During Prehandover Preparation
Yang, X. J., Wickens, C. D., Park, T., Fong, L., & Siah, K. T. H. (2015) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815598889 · Cited by 13
Just-in-Time Encoding Into Visual Working Memory Is Contingent Upon Constant Availability of External Information
Hoogerbrugge, A. J., Strauch, C., Böing, S., Nijboer, T. C. W., & der Stigchel, S. V. (2024) · Journal of Cognition · doi:10.5334/joc.364 · Cited by 13
An empirical investigation into how users adapt to mobile phone auto-locks in a multitask setting
Brumby, D. P., & Seyedi, V. (2012) · International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI) · doi:10.1145/2371574.2371616 · Cited by 11
Children’s adaptive pre-decisional search behavior: Effects of memory and number of alternatives
Katz, I., Bereby‐Meyer, Y., Assor, A., & Danziger, S. (2009) · Journal of Economic Psychology · doi:10.1016/j.joep.2009.09.003 · Cited by 12
A tutorial on DynaSearch: A Web-based system for collecting process-tracing data in dynamic decision tasks
Lindell, M. K., House, D. H., Gestring, J., & Wu, H. (2018) · Behavior Research Methods · doi:10.3758/s13428-018-1119-3 · Cited by 11
Does task sustainability provide a unified measure of subjective task difficulty?
Rosenbaum, D. Α., & Bui, B. V. (2019) · Psychonomic Bulletin & Review · doi:10.3758/s13423-019-01631-8 · Cited by 11
Perseveration on cognitive strategies
Weis, P. P., & Kunde, W. (2023) · Memory & Cognition · doi:10.3758/s13421-023-01475-7 · Cited by 11
Personal Rapid Transit and Its Development
McDonald, S. S. (2013) · Springer eBooks · doi:10.1007/978-1-4614-5844-9_671 · Cited by 11
7 Dynamical Systems Theory
Rupert, R. D. (2009) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195379457.003.0007 · Cited by 11
Representation control increases task efficiency in complex graphical representations
Moritz, J., Meyerhoff, H. S., Meyer-Dernbecher, C., & Schwan, S. (2018) · PLOS ONE · doi:10.1371/journal.pone.0196420 · Cited by 11
Effort avoidance is not simply error avoidance
Feghhi, I., & Rosenbaum, D. Α. (2020) · Psychological Research · doi:10.1007/s00426-020-01331-2 · Cited by 11
Verbalization of Decision Strategies in Multiple‐Cue Probabilistic Inference
Walsh, M. M., & Gluck, K. A. (2015) · Journal of Behavioral Decision Making · doi:10.1002/bdm.1878 · Cited by 11
Designing information fusion for the encoding of visual–spatial information
Waldron, S. M., Patrick, J., Duggan, G. B., Banbury, S. P., & Howes, A. (2008) · Ergonomics · doi:10.1080/00140130701811933 · Cited by 11
Cognitive Modeling for Cognitive Engineering
Gray, W. D. (2001) · Cambridge University Press eBooks · doi:10.1017/cbo9780511816772.025 · Cited by 11
Self-citation
Collaborative problem solving: The role of team knowledge building processes and external representations
Rosen, M. A. (2010) · ProQuest Demo Repository · Cited by 11
Increasing Accuracy by Decreasing Presentation Quality in Transcription Tasks
Soboczenski, F., Cairns, P. A., & Cox, A. L. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40480-1_25 · Cited by 10
Testing the rehearsal hypothesis with two FastTap interfaces
Gutwin, C. A., Cockburn, A., & Lafreniere, B. J. (2015) · Proceedings · doi:10.20380/gi2015.29 · Cited by 10
Perceptual processing demands influence voluntary task choice
Mittelstädt, V., Miller, J. O., & Kiesel, A. (2022) · Cognition · doi:10.1016/j.cognition.2022.105232 · Cited by 12
Bounded Optimal State Estimation and Control in Visual Search: Explaining Distractor Ratio Effects
Myers, C. W., Lewis, R. L., & Howes, A. (2013) · eScholarship (California Digital Library) · Cited by 10
Calling while Driving Using Augmented Reality: Blessing or Curse?
Kun, A. L., van der Meulen, H., & Janssen, C. P. (2018) · PRESENCE Virtual and Augmented Reality · doi:10.1162/pres_a_00316 · Cited by 10
Balancing cognitive and environmental constraints when deciding to switch tasks: Exploring self-reported task-selection strategies in self-organised multitasking
Mittelstädt, V., Schaffernak, I., Miller, J. O., & Kiesel, A. (2020) · Quarterly Journal of Experimental Psychology · doi:10.1177/1747021820970079 · Cited by 10
Cognitive systems and the supersized mind
Rupert, R. D. (2010) · Philosophical Studies · doi:10.1007/s11098-010-9600-6 · Cited by 10
More than 8,192 ways to skin a cat: Modeling behavior in multidimensional strategy spaces
Smith, M. R., Lewis, R. L., Howes, A., Chu, A., Green, C., & Vera, A. H. (2008) · Cited by 10
Towards a common code for difficulty: Navigating a narrow gap is like memorizing an extra digit
Feghhi, I., Franchak, J. M., & Rosenbaum, D. Α. (2021) · Attention Perception & Psychophysics · doi:10.3758/s13414-021-02356-4 · Cited by 9
Allocation of cognitive resources in comparative visual search – Individual and task dependent effects
Hardieß, G., & Mallot, H. A. (2015) · Vision Research · doi:10.1016/j.visres.2015.05.017 · Cited by 9
Harder to Access, Better Performance? The Effects of Information Access Cost on Strategy and Performance
Morgan, P. L., Waldron, S. M., King, S. L., & Patrick, J. (2007) · Lecture notes in computer science · doi:10.1007/978-3-540-73345-4_15 · Cited by 9
Acquisition vs. Memorization Trade-Offs Are Modulated by Walking Distance and Pattern Complexity in a Large-Scale Copying Paradigm
Hardieß, G., Basten, K., & Mallot, H. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018494 · Cited by 9
Shifting reliance between the internal and external world: A meta-analysis on visual-working memory use
Qing, T., Strauch, C., van Maanen, L., & der Stigchel, S. V. (2024) · Psychonomic Bulletin & Review · doi:10.3758/s13423-024-02623-z · Cited by 10
The effect of information access cost and overconfidence bias on junior doctors’ pre-handover performance
Yang, X. J., Park, T., Wickens, C. D., Siah, K. T. H., Fong, L., & Yin, S. Q. (2013) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931213571391 · Cited by 8
Computational Model of the Transition from Novice to Expert Interaction Techniques
Bailly, G., Khamassi, M., & Girard, B. (2022) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3505557 · Cited by 11
Benefit-cost trade-offs-based empathic choices
Ge, Y., Li, X., Li, F., Chen, F., Sun, B., & Li, W. (2022) · Personality and Individual Differences · doi:10.1016/j.paid.2022.111875 · Cited by 8
Behavioral Systems Management of Confined Microsocieties: An Agenda for Research and Applications
Emurian, H. H., Canfield, K., Roma, P. G., Gasior, E. D., Brinson, Z. S., Hienz, R. D., Hursh, S. R., & Brady, J. V. (2009) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2009-01-2423 · Cited by 8
A Dynamic Context Model of Interactive Behavior
Fu, W. (2011) · Cognitive Science · doi:10.1111/j.1551-6709.2011.01173.x · Cited by 8
Self-citation
External Working Memory and the Amount of Distributed Cognition
Maeda, N. (2012) · eScholarship (California Digital Library) · Cited by 8
Arranging Objects in Space: Measuring Task‐Relevant Organizational Behaviors During Goal Pursuit
Solman, G. J. F., & Kingstone, A. F. (2016) · Cognitive Science · doi:10.1111/cogs.12391 · Cited by 8
Speed Considerations Can Be of Little Concern When Outsourcing Thought to External Devices
Weis, P. P., & Wiese, E. (2018) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/1541931218621004 · Cited by 6
An Approach to Human-Level Commonsense Reasoning
Anderson, M. L., Gomaa, W. E., Grant, J., & Perlis, D. (2012) · Springer eBooks · doi:10.1007/978-94-007-4438-7_12 · Cited by 7
The effect of strategy game types on inhibition
Leong, A. Y. C., Yong, M. H., & Lin, M.-H. (2022) · Psychological Research · doi:10.1007/s00426-021-01632-0 · Cited by 14
The effect of strategy game types on inhibition
Leong, A. Y. C. *., Yong, M. H., & Lin, M. H. *. (2022) · Sunway Institutional Repository (Sunway University) · Cited by 7
An investigation of the saving‐enhanced memory effect: The role of test order and list saving
Tsai, P., Sachdeva, C., Gilbert, S. J., & Scarampi, C. (2023) · Applied Cognitive Psychology · doi:10.1002/acp.4067 · Cited by 7
Changing perspective: Zooming in and out during visual search.
Solman, G. J. F., Cheyne, J. A., & Smilek, D. (2012) · Journal of Experimental Psychology Human Perception & Performance · doi:10.1037/a0029707 · Cited by 7
Designing Interfaces that Encourage a More Effortful Cognitive Strategy
Morgan, P. L., & Patrick, J. (2010) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193121005400429 · Cited by 7
Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans
Stevens, J. R., Marewski, J. N., Schooler, L. J., & Gilby, I. C. (2016) · Royal Society Open Science · doi:10.1098/rsos.160293 · Cited by 7
Tied to expectations: Predicting features speeds processing even under adverse circumstances
Schwager, S., Gaschler, R., Rünger, D., & Frensch, P. A. (2016) · Memory & Cognition · doi:10.3758/s13421-016-0683-y · Cited by 7
Interruptions, visual cues, and the microstructure of interaction: Four laboratory studies
Weng, M., Huber, S. L., Vilgan, E., Grundgeiger, T., & Sanderson, P. M. (2017) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2017.02.002 · Cited by 7
The Price is Right: A High Information Access Cost Facilitates Category Learning
Wood, M. J., Fry, M., & Blair, M. R. (2010) · eScholarship (California Digital Library) · Cited by 7
Which cognitive tools do we prefer to use, and is that preference rational?
Alexandre, B., Navarro, J., Reynaud, E., & Osiurak, F. (2019) · Cognition · doi:10.1016/j.cognition.2019.02.005 · Cited by 7
Steps Towards Integrated Models of Cognitive Systems: A Levels-of-Analysis Approach to Comparing Human Performance to Model Predictions in a Complex Task Environment
Schoelles, M. J., Neth, H., Myers, C. W., & Gray, W. D. (2006) · KOPS (University of Konstanz) · Cited by 7
Self-citation
Switching between different cognitive strategies induces switch costs as evidenced by switches between manual and mental object rotation
Weis, P. P., & Kunde, W. (2024) · Scientific Reports · doi:10.1038/s41598-024-56836-2 · Cited by 8
Comparing target detection errors in visual search and manually-assisted search
Solman, G. J. F., Hickey, K., & Smilek, D. (2014) · Attention Perception & Psychophysics · doi:10.3758/s13414-014-0641-3 · Cited by 6
Unified Modeling of Proactive Interference and Memorization Effort: A new mathematical perspective within ACT-R theory.
Das, A., & Stuerzlinger, W. (2013) · eScholarship (California Digital Library) · Cited by 6
Age differences in motivation drive performance during the sustained attention to response task
Hanzal, S., Learmonth, G., Thut, G., & Harvey, M. (2025) · PLoS ONE · doi:10.1371/journal.pone.0324694 · Cited by 5
Judgements of effort as a function of post-trial versus post-task elicitation
Ashburner, M., & Risko, E. F. (2021) · Quarterly Journal of Experimental Psychology · doi:10.1177/17470218211005759 · Cited by 5
Age‐related advantage for recall of complex naturalistic information following cognitive offloading
Burnett, L. K., & Richmond, L. L. (2024) · Applied Cognitive Psychology · doi:10.1002/acp.4217 · Cited by 5
PHEVs and BEVs in Coupled Power and Transportation Systems
Kezunović, M., & Waller, S. T. (2012) · Springer eBooks · doi:10.1007/978-1-0716-1492-1_824 · Cited by 5
Squeezing the Balloon: Analyzing the Unpredictable Effects of Cognitive Workload
Ralph, J., Gray, W. D., & Schoelles, M. J. (2010) · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · doi:10.1177/154193121005400407 · Cited by 5
Self-citation
Cognition, material culture and religious ritual
Krátký, J. (2012) · Journal of the British Association for the Study of Religion (JBASR) · doi:10.1558/jbasr.32487 · Cited by 5
The psychology of task management: The smaller tasks trap
Rusou, Z., Amar, M., & Ayal, S. (2020) · Judgment and Decision Making · doi:10.1017/s1930297500007518 · Cited by 5

Authors: Gray, W. D., Sims, C. R., Fu, W.-T., & Schoelles, M. J.
Affiliations: Rensselaer Polytechnic Institute (US)
University of Illinois Urbana-Champaign (US)
ORCID: Gray, Wayne D.
Sims, Chris R.
Venue: Psychological Review
Publisher: American Psychological Association (APA)
Published: 2006
Volume: 113
Issue: 3
Pages: 461-482
ISSN: 0033-295X (ISSN-L)
1939-1471
DOI: 10.1037/0033-295x.113.3.461
OpenAlex: W2104514002
Cited by: 360
References: 104
Citations by year: 2026: 13 · 2025: 7 · 2024: 15 · 2023: 9 · 2022: 14 · 2021: 15 · 2020: 14 · 2019: 14 · 2018: 15 · 2017: 15 · 2016: 14 · 2015: 19 · 2014: 23 · 2013: 27 · 2012: 24
FWCI: 13.37
Type: journal article
Language: en
Open access: closed
Locations: Psychological Review (publishedVersion)
PubMed (publishedVersion)
Defense Technical Information Center (DTIC) (submittedVersion)
Funders: Office of Naval Research (N000140310046)
Air Force Office of Scientific Research (F49620-03-1-0143)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Life Sciences › Neuroscience › Cognitive Neuroscience › Embodied and Extended Cognition
Life Sciences › Neuroscience › Cognitive Neuroscience › Motor Control and Adaptation
Keywords: resource allocation, cognitive effort, ACT-R, reinforcement learning, expected utility, interactive behavior
MeSH terms: Cognition, Humans, Interpersonal Relations, Models, Psychological, Psychological Theory, Reinforcement, Psychology, Social 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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

The soft constraints hypothesis: A rational analysis approach to resource allocation for interactive behavior.

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks