The Experts below are selected from a list of 76446 Experts worldwide ranked by ideXlab platform
Thomas L Griffiths - One of the best experts on this subject based on the ideXlab platform.
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the efficiency of Human Cognition reflects planned information processing
arXiv: Artificial Intelligence, 2020Co-Authors: Mark K Ho, David Abel, Jonathan D Cohen, Michael L Littman, Thomas L GriffithsAbstract:Planning is useful. It lets people take actions that have desirable long-term consequences. But, planning is hard. It requires thinking about consequences, which consumes limited computational and cognitive resources. Thus, people should plan their actions, but they should also be smart about how they deploy resources used for planning their actions. Put another way, people should also "plan their plans". Here, we formulate this aspect of planning as a meta-reasoning problem and formalize it in terms of a recursive Bellman objective that incorporates both task rewards and information-theoretic planning costs. Our account makes quantitative predictions about how people should plan and meta-plan as a function of the overall structure of a task, which we test in two experiments with Human participants. We find that people's reaction times reflect a planned use of information processing, consistent with our account. This formulation of planning to plan provides new insight into the function of hierarchical planning, state abstraction, and cognitive control in both Humans and machines.
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resource rational analysis understanding Human Cognition as the optimal use of limited computational resources
Behavioral and Brain Sciences, 2020Co-Authors: Falk Lieder, Thomas L GriffithsAbstract:Modeling Human Cognition is challenging because there are infinitely many mechanisms that can generate any given observation. Some researchers address this by constraining the hypothesis space through assumptions about what the Human mind can and cannot do, while others constrain it through principles of rationality and adaptation. Recent work in economics, psychology, neuroscience, and linguistics has begun to integrate both approaches by augmenting rational models with cognitive constraints, incorporating rational principles into cognitive architectures, and applying optimality principles to understanding neural representations. We identify the rational use of limited resources as a unifying principle underlying these diverse approaches, expressing it in a new cognitive modeling paradigm called resource-rational analysis . The integration of rational principles with realistic cognitive constraints makes resource-rational analysis a promising framework for reverse-engineering cognitive mechanisms and representations. It has already shed new light on the debate about Human rationality and can be leveraged to revisit classic questions of cognitive psychology within a principled computational framework. We demonstrate that resource-rational models can reconcile the mind's most impressive cognitive skills with people's ostensive irrationality. Resource-rational analysis also provides a new way to connect psychological theory more deeply with artificial intelligence, economics, neuroscience, and linguistics.
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rational analysis as a link between Human memory and information retrieval
2008Co-Authors: Mark Steyvers, Thomas L GriffithsAbstract:Rational analysis has been successful in explaining a variety of different aspects of Human Cognition (Anderson, 1990; Chater & Oaksford, 1999; Marr, 1982; Oaksford & Chater, 1998). The explanations provided by rational analysis have two properties: they emphasize the connection between behavior and the structure of the environment, and they focus on the abstract computational problems being solved. These properties provide the opportunity to recognize connections between Human Cognition and other systems that solve the same computational problems, with the potential both to provide new insights into Human Cognition and to allow us to develop better systems for solving those problems. In particular, we should expect to find a correspondence between Human Cognition and systems that are successful at solving the same computational problems in a similar environment. In this chapter, we argue that such a correspondence exists between Human memory and internet search, and show that this correspondence leads to both better models of Human Cognition, and better methods for searching the web. Anderson (1990) and Anderson and Schooler (1991, 2000) have shown that many findings in the memory literature related to reCognition and recall of lists of words can be understood by considering the computational problem of assessing the relevance of an item in memory to environmental cues. They showed a close correspondence between memory retrieval for lists of words and statistical patterns of occurrence of words in large databases of text. Similarly, other computational models for memory (Shiffrin & Steyvers, 1997), association (Griffiths et al., 2007), reasoning (Oaksford & Chater, 1994), prediction (Griffiths & Tenenbaum, 2006) and causal 15-Charter&Oaksford-Chap15 11/3/07 5:27 PM Page 327
David G Rand - One of the best experts on this subject based on the ideXlab platform.
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evolutionary game dynamics of controlled and automatic decision making
Chaos, 2015Co-Authors: Danielle F P Toupo, Jonathan D Cohen, Steven H Strogatz, David G RandAbstract:We integrate dual-process theories of Human Cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and Human Cognition and suggest necessary conditions for the rise and fall of rationality.
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evolutionary game dynamics of controlled and automatic decision making
arXiv: Dynamical Systems, 2015Co-Authors: Danielle F P Toupo, Jonathan D Cohen, Steven H Strogatz, David G RandAbstract:We integrate dual-process theories of Human Cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model where agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible, and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions where having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and Human Cognition, and demonstrate necessary conditions for the rise and fall of rationality.
Jonathan D Cohen - One of the best experts on this subject based on the ideXlab platform.
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the efficiency of Human Cognition reflects planned information processing
arXiv: Artificial Intelligence, 2020Co-Authors: Mark K Ho, David Abel, Jonathan D Cohen, Michael L Littman, Thomas L GriffithsAbstract:Planning is useful. It lets people take actions that have desirable long-term consequences. But, planning is hard. It requires thinking about consequences, which consumes limited computational and cognitive resources. Thus, people should plan their actions, but they should also be smart about how they deploy resources used for planning their actions. Put another way, people should also "plan their plans". Here, we formulate this aspect of planning as a meta-reasoning problem and formalize it in terms of a recursive Bellman objective that incorporates both task rewards and information-theoretic planning costs. Our account makes quantitative predictions about how people should plan and meta-plan as a function of the overall structure of a task, which we test in two experiments with Human participants. We find that people's reaction times reflect a planned use of information processing, consistent with our account. This formulation of planning to plan provides new insight into the function of hierarchical planning, state abstraction, and cognitive control in both Humans and machines.
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evolutionary game dynamics of controlled and automatic decision making
Chaos, 2015Co-Authors: Danielle F P Toupo, Jonathan D Cohen, Steven H Strogatz, David G RandAbstract:We integrate dual-process theories of Human Cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model in which agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions in which having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and Human Cognition and suggest necessary conditions for the rise and fall of rationality.
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evolutionary game dynamics of controlled and automatic decision making
arXiv: Dynamical Systems, 2015Co-Authors: Danielle F P Toupo, Jonathan D Cohen, Steven H Strogatz, David G RandAbstract:We integrate dual-process theories of Human Cognition with evolutionary game theory to study the evolution of automatic and controlled decision-making processes. We introduce a model where agents who make decisions using either automatic or controlled processing compete with each other for survival. Agents using automatic processing act quickly and so are more likely to acquire resources, but agents using controlled processing are better planners and so make more effective use of the resources they have. Using the replicator equation, we characterize the conditions under which automatic or controlled agents dominate, when coexistence is possible, and when bistability occurs. We then extend the replicator equation to consider feedback between the state of the population and the environment. Under conditions where having a greater proportion of controlled agents either enriches the environment or enhances the competitive advantage of automatic agents, we find that limit cycles can occur, leading to persistent oscillations in the population dynamics. Critically, however, these limit cycles only emerge when feedback occurs on a sufficiently long time scale. Our results shed light on the connection between evolution and Human Cognition, and demonstrate necessary conditions for the rise and fall of rationality.
Dominic Palmerbrown - One of the best experts on this subject based on the ideXlab platform.
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rumelhart prize to be announced at cognitive science society
Trends in Cognitive Sciences, 2001Co-Authors: Dominic PalmerbrownAbstract:The David E. Rumelhart Prize will be awarded for the first time in 2001. The award is for recent, significant contributions to the formal analysis of Human Cognition and will go either to an individual or to a team. The scope of research eligible for the award includes mathematical modelling of Human cognitive processes, formal analysis of language and other products of Human cognitive activity, and computational analyses of Human Cognition. The prize, which includes a monetary award of $100,000, will be funded by the Robert J. Glushko and Pamela Samuelson Foundation in San Francisco.The first winner will be announced at the meeting of the Cognitive Science Society in Edinburgh this summer (COGSCI 2001, 1–4 August). The recipient will deliver the Prize Lecture at the subsequent meeting, at George Mason University, in 2002. James L. McClelland chairs the selection panel and full details are available at http://www.cnbc.cmu.edu/derprize/. This site also provides information on David Rumelhart himself and his belief that cognitive science should have formal theories, such as those in linguistics, as well as mathematical and computational models.
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rumelhart prize to be announced at cognitive science society
Trends in Cognitive Sciences, 2001Co-Authors: Dominic PalmerbrownAbstract:The David E. Rumelhart Prize will be awarded for the first time in 2001. The award is for recent, significant contributions to the formal analysis of Human Cognition and will go either to an individual or to a team. The scope of research eligible for the award includes mathematical modelling of Human cognitive processes, formal analysis of language and other products of Human cognitive activity, and computational analyses of Human Cognition. The prize, which includes a monetary award of $100,000, will be funded by the Robert J. Glushko and Pamela Samuelson Foundation in San Francisco.The first winner will be announced at the meeting of the Cognitive Science Society in Edinburgh this summer (COGSCI 2001, 1–4 August). The recipient will deliver the Prize Lecture at the subsequent meeting, at George Mason University, in 2002. James L. McClelland chairs the selection panel and full details are available at http://www.cnbc.cmu.edu/derprize/. This site also provides information on David Rumelhart himself and his belief that cognitive science should have formal theories, such as those in linguistics, as well as mathematical and computational models.
Falk Lieder - One of the best experts on this subject based on the ideXlab platform.
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resource rational analysis understanding Human Cognition as the optimal use of limited computational resources
Behavioral and Brain Sciences, 2020Co-Authors: Falk Lieder, Thomas L GriffithsAbstract:Modeling Human Cognition is challenging because there are infinitely many mechanisms that can generate any given observation. Some researchers address this by constraining the hypothesis space through assumptions about what the Human mind can and cannot do, while others constrain it through principles of rationality and adaptation. Recent work in economics, psychology, neuroscience, and linguistics has begun to integrate both approaches by augmenting rational models with cognitive constraints, incorporating rational principles into cognitive architectures, and applying optimality principles to understanding neural representations. We identify the rational use of limited resources as a unifying principle underlying these diverse approaches, expressing it in a new cognitive modeling paradigm called resource-rational analysis . The integration of rational principles with realistic cognitive constraints makes resource-rational analysis a promising framework for reverse-engineering cognitive mechanisms and representations. It has already shed new light on the debate about Human rationality and can be leveraged to revisit classic questions of cognitive psychology within a principled computational framework. We demonstrate that resource-rational models can reconcile the mind's most impressive cognitive skills with people's ostensive irrationality. Resource-rational analysis also provides a new way to connect psychological theory more deeply with artificial intelligence, economics, neuroscience, and linguistics.
