Rational use of cognitive resources in human planning

Making good decisions requires thinking ahead, but the huge number of actions and outcomes one could consider makes exhaustive planning infeasible for computationally constrained agents, such as humans. How people are nevertheless able to solve novel problems when their actions have long-reaching consequences is thus a long-standing question in cognitive science. To address this question, we propose a model of resource-constrained planning that allows us to derive optimal planning strategies. We find that previously proposed heuristics such as best-first search are near-optimal under some circumstances, but not others. In a mouse-tracking paradigm, we show that people adapt their planning strategies accordingly, planning in a manner that is broadly consistent with the optimal model but not with any single heuristic model. We also find systematic deviations from the optimal model that might result from additional cognitive constraints that are yet to be uncovered.

Rational Use ofCognitive Resources…Rational Use of Cognitive Resources: Levels of Analysis Between the Computational and the AlgorithmicHeuristic DecisionMakingHeuristic Decision MakingComputationalRationality: Linking…Computational Rationality: Linking Mechanism and Behavior Through Bounded Utility MaximizationComputationalrationality: A…Computational rationality: A converging paradigm for intelligence in brains, minds, and machinesInterplay of approximateplanning strategiesInterplay of approximate planning strategiesAdaptive integration ofhabits into…Adaptive integration of habits into depth-limited planning defines a habitual-goal–directed spectrumStrategy selection asrational metareasoning.Strategy selection as rational metareasoning.Cost-Benefit ArbitrationBetween Multiple…Cost-Benefit Arbitration Between Multiple Reinforcement-Learning SystemsFixation patterns insimple choice reflect…Fixation patterns in simple choice reflect optimal information samplingResource-rationalanalysis: Understanding…Resource-rational analysis: Understanding human cognition as the optimal use of limited computational resourcesDoing more with less:meta-reasoning and…Doing more with less: meta-reasoning and meta-learning in humans and machinesRevealing the impact ofexpertise on human…Revealing the impact of expertise on human planning with a two-player board gameFormalizing planning andinformation search in…Formalizing planning and information search in naturalistic decision-makingAutomatic Discovery ofInterpretable Planning…Automatic Discovery of Interpretable Planning StrategiesAdvances in modelinglearning and…Advances in modeling learning and decision-making in neuroscienceTime Spent Thinking inOnline Chess Reflects…Time Spent Thinking in Online Chess Reflects the Value of ComputationDeep imagination is aclose to optimal policy…Deep imagination is a close to optimal policy for planning in large decision trees under limited resourcesLeveraging artificialintelligence to improve…Leveraging artificial intelligence to improve people’s planning strategiesBoosting humandecision-making with…Boosting human decision-making with AI-generated decision aidsActive causal structurelearning in continuous…Active causal structure learning in continuous timeExpertise increasesplanning depth in human…Expertise increases planning depth in human gameplayTowards machines thatunderstand peopleTowards machines that understand peopleBuilding Machines thatLearn and Think with…Building Machines that Learn and Think with PeopleResource-RationalVirtual Bargaining for…Resource-Rational Virtual Bargaining for Moral Judgment: Toward a Probabilistic Cognitive ModelRational use ofcognitive resources in…Rational use of cognitive resources in human planning過去の参考文献中心の論文この論文を引用する論文古い新しい

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