[Coggroup] ANIMAL COGNITION AND AI by Murray Shanahan (Imperial College & DeepMind): Sept 29, 10:30am
Animal Cognition and AI
Murray Shanahan Cognitive Robotics, Imperial College & DeepMind
UQÀM ISC DIC CRIA Cognitive Informatics Seminar
September 29, 2022 Thursday, 10:30 am Zoom: https://uqam.zoom.us/j/88481835073 Abstract: Common sense in humans is founded on a set of basic capacities that are possessed by many other animals, capacities pertaining to the understanding of objects, space, and causality. The field of animal cognition has developed numerous experimental protocols for studying these capacities and, thanks to progress in deep reinforcement learning (RL), it is now possible to apply these methods directly to evaluate RL agents in 3D environments. The Animal-AI Environment aims to apply the ability-oriented testing used in comparative psychology to AI systems. Besides evaluation, the animal cognition literature offers a rich source of behavioural data, which can serve as inspiration for RL tasks and curricula.
Bio: Murray Shanahan is Professor of Cognitive Robotics at Imperial College London and Senior Research Scientist at DeepMind. His publications span artificial intelligence, robotics, logic, dynamical systems, computational neuroscience, and philosophy of mind. His work up to 2000 was in the tradition of classical, symbolic AI. He then turned his attention to the brain and its embodiment. His current interests include neurodynamics, consciousness, machine learning, and the impacts of artificial intelligence.
References:
Shanahan, M., Crosby, M., Beyret, B., & Cheke, L. (2020). Artificial intelligence and the common sense of animalshttps://www.sciencedirect.com/science/article/pii/S1364661320302163. Trends in cognitive sciences, 24(11), 862-872.
Voudouris, K., Crosby, M., Beyret, B., Hernández-Orallo, J., Shanahan, M., Halina, M., & Cheke, L. G. (2022). Direct Human-AI Comparison in the Animal-AI Environmenthttps://www.frontiersin.org/articles/10.3389/fpsyg.2022.711821/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Psychology&id=711821. Frontiers in Psychology, 1884.
Shanahan, M., & Mitchell, M. (2022). Abstraction for Deep Reinforcement Learninghttps://arxiv.org/pdf/2202.05839.pdf. UCAI 2022 arXiv preprint arXiv:2202.05839.
Shanahan, M., Embodiment and the Inner Life: Cognition and Consciousness in the Space of Possible Mindshttps://www.doc.ic.ac.uk/~mpsha/EIL.html, Oxford University Press (2010). Full texthttps://www.doc.ic.ac.uk/~mpsha/ShanahanBook2010.pdf
Animal Cognition and AI
Murray Shanahan Cognitive Robotics, Imperial College & DeepMind
UQÀM ISC DIC CRIA Cognitive Informatics Seminar
September 29, 2022 Thursday, 10:30 am Zoom: https://uqam.zoom.us/j/88481835073 Abstract: Common sense in humans is founded on a set of basic capacities that are possessed by many other animals, capacities pertaining to the understanding of objects, space, and causality. The field of animal cognition has developed numerous experimental protocols for studying these capacities and, thanks to progress in deep reinforcement learning (RL), it is now possible to apply these methods directly to evaluate RL agents in 3D environments. The Animal-AI Environment aims to apply the ability-oriented testing used in comparative psychology to AI systems. Besides evaluation, the animal cognition literature offers a rich source of behavioural data, which can serve as inspiration for RL tasks and curricula.
Murray Shanahan is Professor of Cognitive Robotics at Imperial College London and Senior Research Scientist at DeepMind. His publications span artificial intelligence, robotics, logic, dynamical systems, computational neuroscience, and philosophy of mind. His work up to 2000 was in the tradition of classical, symbolic AI. He then turned his attention to the brain and its embodiment. His current interests include neurodynamics, consciousness, machine learning, and the impacts of artificial intelligence.
References:
Shanahan, M., Crosby, M., Beyret, B., & Cheke, L. (2020). Artificial intelligence and the common sense of animalshttps://www.sciencedirect.com/science/article/pii/S1364661320302163. Trends in cognitive sciences, 24(11), 862-872.
Voudouris, K., Crosby, M., Beyret, B., Hernández-Orallo, J., Shanahan, M., Halina, M., & Cheke, L. G. (2022). Direct Human-AI Comparison in the Animal-AI Environmenthttps://www.frontiersin.org/articles/10.3389/fpsyg.2022.711821/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Psychology&id=711821. Frontiers in Psychology, 1884.
Shanahan, M., & Mitchell, M. (2022). Abstraction for Deep Reinforcement Learninghttps://arxiv.org/pdf/2202.05839.pdf. UCAI 2022 arXiv preprint arXiv:2202.05839.
Shanahan, M., Embodiment and the Inner Life: Cognition and Consciousness in the Space of Possible Mindshttps://www.doc.ic.ac.uk/~mpsha/EIL.html, Oxford University Press (2010). Full texthttps://www.doc.ic.ac.uk/~mpsha/ShanahanBook2010.pdf
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Stevan R. Harnad, Dr.