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“The Origins of Intelligence In The Child”
Margaret Cook · 1923
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“The Origins of Intelligence In The Child”
Margaret Cook · 1923
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“An apparatus for the study of animal behavior”
WT Heron and BF Skinner · 1939
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“An apparatus for the study of animal behavior”
WT Heron and BF Skinner · 1939
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“Reinforcement today.”
Burrhus Skinner · 1958
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“Reinforcement today.”
Burrhus Skinner · 1958
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“Intellectual operations and their development”
Jean Piaget and Bärbel Inhelder · 1969
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“Intellectual operations and their development”
Jean Piaget and Bärbel Inhelder · 1969
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“Theory of feeding strategies”
Thomas Schoener · 1971
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“Theory of feeding strategies”
Thomas Schoener · 1971
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“Optimal foraging: a selective review of theory and tests”
Graham Pyke, H Pulliam and Eric Charnov · 1977
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“Optimal foraging: a selective review of theory and tests”
Graham Pyke, H Pulliam and Eric Charnov · 1977
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“Brain and intelligence in vertebrates”
E.. Macphail · 1982
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“Brain and intelligence in vertebrates”
E.. Macphail · 1982
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“Object knowledge in infancy: Current controversies and approaches”
Denis Mareschal · 2000
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“Object knowledge in infancy: Current controversies and approaches”
Denis Mareschal · 2000
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“A day of great illumination: B F Skinner’s discovery of shaping”
Gail Peterson · 2004
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“A day of great illumination: B F Skinner’s discovery of shaping”
Gail Peterson · 2004
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“Humans have evolved specialized skills of social cognition: The cultural intelligence hypothesis”
Esther Herrmann et al · 2007
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“Object persistence in philosophy and psychology”
Brian Scholl · 2007
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“Humans have evolved specialized skills of social cognition: The cultural intelligence hypothesis”
Esther Herrmann et al · 2007
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“Object persistence in philosophy and psychology”
Brian Scholl · 2007
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“MuJoCo: A physics engine for model-based control.”
Emanuel Todorov, Tom Erez and Yuval Tassa · 2012
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“MuJoCo: A physics engine for model-based control.”
Emanuel Todorov, Tom Erez and Yuval Tassa · 2012
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“Playing atari with deep reinforcement learning”
Volodymyr Mnih et al · 2013
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“Playing atari with deep reinforcement learning”
Volodymyr Mnih et al · 2013
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“Crowdsourcing for Cognitive Science – The Utility of Smartphones”
Harriet. Brown et al · 2014
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“Do animals understand invisible displacement? A critical review.”
Kelly Jaakkola · 2014
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“Tracing the trajectory of skill learning with a very large sample of online game players”
Tom Stafford and Michael Dewar · 2014
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“Crowdsourcing for Cognitive Science – The Utility of Smartphones”
Harriet. Brown et al · 2014
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“Do animals understand invisible displacement? A critical review.”
Kelly Jaakkola · 2014
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“Tracing the trajectory of skill learning with a very large sample of online game players”
Tom Stafford and Michael Dewar · 2014
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“Fitting Linear Mixed-Effects Models Using lme4”
Douglas Bates, Martin Mächler, Ben Bolker and Steve Walker · 2015
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“Perception of object persistence: The origins of object permanence in infancy”
J Bremner, Alan Slater and Scott Johnson · 2015
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“Manifesto for a new (computational) cognitive revolution”
Thomas. Griffiths · 2015
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“Age-related changes in working memory and the ability to ignore distraction”
Fiona McNab et al · 2015
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“Fitting Linear Mixed-Effects Models Using lme4”
Douglas Bates, Martin Mächler, Ben Bolker and Steve Walker · 2015
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“Perception of object persistence: The origins of object permanence in infancy”
J Bremner, Alan Slater and Scott Johnson · 2015
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“Manifesto for a new (computational) cognitive revolution”
Thomas. Griffiths · 2015
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“Age-related changes in working memory and the ability to ignore distraction”
Fiona McNab et al · 2015
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Charles Beattie et al · 2016
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“The Malmo Platform for Artificial Intelligence Experimentation.”
Matthew Johnson, Katja Hofmann, Tim Hutton and David Bignell · 2016
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Charles Beattie et al · 2016
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“The Malmo Platform for Artificial Intelligence Experimentation.”
Matthew Johnson, Katja Hofmann, Tim Hutton and David Bignell · 2016
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“The measure of all minds: evaluating natural and artificial intelligence”
José Hernández-Orallo · 2017
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“Building machines that learn and think like people”
Brenden Lake, Tomer Ullman, Joshua Tenenbaum and Samuel Gershman · 2017
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“Proximal policy optimization algorithms”
John Schulman et al · 2017
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“Creativity in online gaming: Individual and dyadic performance in Minecraft”
Alexander. Voiskounsky, Tatiana. Yermolova, Sergey. Yagolkovskiy and Valeria. Khromova · 2017
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“The measure of all minds: evaluating natural and artificial intelligence”
José Hernández-Orallo · 2017
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“Building machines that learn and think like people”
Brenden Lake, Tomer Ullman, Joshua Tenenbaum and Samuel Gershman · 2017
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“Proximal policy optimization algorithms”
John Schulman et al · 2017
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“Creativity in online gaming: Individual and dyadic performance in Minecraft”
Alexander. Voiskounsky, Tatiana. Yermolova, Sergey. Yagolkovskiy and Valeria. Khromova · 2017
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“Dopamine: A research framework for deep reinforcement learning”
Pablo Castro et al · 2018
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“Global Determinants of Navigation Ability”
Antoine Coutrot et al · 2018
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“Investigating human priors for playing video games”
Rachit Dubey et al · 2018
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“Unity: A general platform for intelligent agents”
Arthur Juliani et al · 2018
Cited alongside, same era.
“Serious games to assess mild cognitive impairment: ‘The game is the assessment”’
Kyle Leduc-McNiven et al · 2018
Cited alongside, same era.
“Psychlab: a psychology laboratory for deep reinforcement learning agents”
Joel Leibo et al · 2018
Cited alongside, same era.
“Dopamine: A research framework for deep reinforcement learning”
Pablo Castro et al · 2018
Cited alongside, same era.
“Minedojo: Building open-ended embodied agents with internet-scale knowledge”
Linxi Fan et al · 2022
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“Optimal foraging”
Andrew King and Harry Marshall · 2022
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“Detect, understand, act: A neuro-symbolic hierarchical reinforcement learning framework”
Ludovico Mitchener, David Tuckey, Matthew Crosby and Alessandra Russo · 2022
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“Intuitive physics learning in a deep-learning model inspired by developmental psychology”
Luis Piloto, Ari Weinstein, Peter Battaglia and Matthew Botvinick · 2022
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“Inductive biases in theory-based reinforcement learning”
Thomas Pouncy and Samuel. Gershman · 2022
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“Digital Games for Creativity Assessment: Strengths, Weaknesses and Opportunities”
Janet Rafner et al · 2022
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“Global Determinants of Navigation Ability”
Antoine Coutrot et al · 2018
Cited alongside, same era.
“Investigating human priors for playing video games”
Rachit Dubey et al · 2018
Cited alongside, same era.
“Unity: A general platform for intelligent agents”
Arthur Juliani et al · 2018
Cited alongside, same era.
“Serious games to assess mild cognitive impairment: ‘The game is the assessment”’
Kyle Leduc-McNiven et al · 2018
Cited alongside, same era.
“Psychlab: a psychology laboratory for deep reinforcement learning agents”
Joel Leibo et al · 2018
Cited alongside, same era.
“The Animal-AI Environment: Training and Testing Animal-Like Artificial Cognition”
Benjamin Beyret et al · 2019
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“Toward personalized cognitive diagnostics of at-genetic-risk Alzheimer’s disease”
Gillian Coughlan et al · 2019
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“Direct human-AI comparison in the Animal-AI environment”
Konstantinos Voudouris et al · 2022
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“Evaluating object permanence in embodied agents using the Animal-AI environment”
Konstantinos Voudouris et al · 2022
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“Avalon: A Benchmark for RL Generalization Using Procedurally Generated Worlds”
Joshua Albrecht et al · 2022
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“Chimpanzees (Pan troglodytes) navigate to find hidden fruit in a virtual environment”
Matthias Allritz et al · 2022
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“CogEnv: A Reinforcement Learning Environment for Cognitive Tests”
Morteza Ansarinia et al · 2022
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“Yoking-Based Identification of Learning Behavior in Artificial and Biological Agents”
Manuel Baum et al · 2022
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“Entropy of city street networks linked to future spatial navigation ability”
A. Coutrot et al · 2022
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“Minedojo: Building open-ended embodied agents with internet-scale knowledge”
Linxi Fan et al · 2022
Later among the works it cites.
“Optimal foraging”
Andrew King and Harry Marshall · 2022
Later among the works it cites.
“Detect, understand, act: A neuro-symbolic hierarchical reinforcement learning framework”
Ludovico Mitchener, David Tuckey, Matthew Crosby and Alessandra Russo · 2022
Later among the works it cites.
“Intuitive physics learning in a deep-learning model inspired by developmental psychology”
Luis Piloto, Ari Weinstein, Peter Battaglia and Matthew Botvinick · 2022
Later among the works it cites.
“Inductive biases in theory-based reinforcement learning”
Thomas Pouncy and Samuel. Gershman · 2022
Later among the works it cites.
“Digital Games for Creativity Assessment: Strengths, Weaknesses and Opportunities”
Janet Rafner et al · 2022
Later among the works it cites.
“Direct human-AI comparison in the Animal-AI environment”
Konstantinos Voudouris et al · 2022
Later among the works it cites.
“Evaluating object permanence in embodied agents using the Animal-AI environment”
Konstantinos Voudouris et al · 2022
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“Using Games to Understand the Mind”
Kelsey Allen et al · 2023
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Franziska Brändle et al · 2023
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Johanni Brea, Nicola Clayton and Wulfram Gerstner · 2023
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“The Future is Computational Comparative Cognition”
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