Planning and construal
computing > AI
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computing > AI > planning
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computing > AI > problem-solving

Task construal: forming a representation of the task. Awareness sampling: ask the participant whether they were aware of something.
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R. Sutton, A. Barto
1998
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An Investigation of Visual Search as a Means of Analyzing Heuristics
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People construct simplified mental representations to plan.
Mark K. Ho, David Abel, Carlos G Correa et al.
2021Nature
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On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, E. Adeli et al.
2021ArXiv
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A Generalist Agent
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2022ArXiv
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T. Griffiths
2015Cognition
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2021Neuroscience and Biobehavioral Reviews
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A. Shenhav, Sebastian Musslick, Falk Lieder et al.
2017Annual Review of Neuroscience
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Hidden processes in structural representations: A reply to Abbott, Austerweil, and Griffiths (2015).
Michael N. Jones, Thomas T. Hills, P. Todd et al.
2015Psychology Review
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Cognitive Control as Cost-Benefit Decision Making
Wouter Kool, Amitai Shenhav, Matthew M. Botvinick et al.
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The Wiley Handbook of Cognitive Control
T. Egner
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Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the Algorithmic
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2015Topics in Cognitive Science
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Novelty and Inductive Generalization in Human Reinforcement Learning
S. Gershman, Y. Niv
2015Topics in Cognitive Science
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L. Barsalou
1983Memory & Cognition
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Learning to Act Using Real-Time Dynamic Programming
A. Barto, S. Bradtke, Satinder Singh et al.
1995Artificial Intelligence
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Faster Heuristic Search Algorithms for Planning with Uncertainty and Full Feedback
Blai Bonet, Hector Geffner
2003International Joint Conference on Art...
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Labeled RTDP: Improving the Convergence of Real-Time Dynamic Programming
Blai Bonet, Hector Geffner
2003International Conference on Automated...
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A Formal Basis for the Heuristic Determination of Minimum Cost Paths
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1968IEEE Transactions on Systems Science ...
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A Framework for Reinforcement Learning and Planning
T. Moerland, J. Broekens, C. Jonker et al.
2020ArXiv
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Abstraction-Guided Sampling for Motion Planning
S. Kiesel, E. Burns, Wheeler Ruml et al.
2021Symposium on Combinatorial Search
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Shakey: From Conception to History
B. Kuipers, E. Feigenbaum, P. Hart et al.
2017The AI Magazine
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Monitoring and control of anytime algorithms: A dynamic programming approach
E. Hansen, S. Zilberstein
2001Artificial Intelligence
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LAO*: A heuristic search algorithm that finds solutions with loops
E. Hansen, S. Zilberstein
2001Artificial Intelligence
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Resource-rational Task Decomposition to Minimize Planning Costs
Carlos G Correa, Mark K. Ho, Frederick Callaway et al.
2020Annual Meeting of the Cognitive Scien...
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Humans decompose tasks by trading off utility and computational cost
Carlos G Correa, Mark K. Ho, Frederick Callaway et al.
2022ArXiv
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Planning with Theory of Mind
M. Ho, R. Saxe, F. Cushman
2022Trends in Cognitive Sciences
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The Problems with Problem Solving: Reflections on the Rise, Current Status, and Possible Future of a Cognitive Research Paradigm
S. Ohlsson
2012Journal of Problem Solving
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Fungal foraging behaviour and hyphal space exploration in micro-structured Soil Chips
Kristin Aleklett, P. Ohlsson, M. Bengtsson et al.
2021The ISME Journal
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On the Utility of Learning about Humans for Human-AI Coordination
Micah Carroll, Rohin Shah, Mark K. Ho et al.
2019Neural Information Processing Systems
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Showing versus doing: Teaching by demonstration
Mark K. Ho, M. Littman, J. MacGlashan et al.
2016NIPS
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Communication in action: Planning and interpreting communicative demonstrations.
Mark K. Ho, F. Cushman, M. Littman et al.
2021Journal of experimental psychology. G...
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Effectively Learning from Pedagogical Demonstrations
Mark K. Ho, M. Littman, F. Cushman et al.
2018Annual Meeting of the Cognitive Scien...
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People Teach With Rewards and Punishments as Communication, Not Reinforcements
Mark K. Ho, F. Cushman, M. Littman et al.
2019Journal of experimental psychology. G...
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