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Learning cognitive maps for vicarious evaluation

View ORCID ProfileRajeev V. Rikhye, Nishad Gothoskar, View ORCID ProfileJ. Swaroop Guntupalli, Antoine Dedieu, View ORCID ProfileMiguel Lázaro-Gredilla, View ORCID ProfileDileep George
doi: https://doi.org/10.1101/864421
Rajeev V. Rikhye
Vicarious AI
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Nishad Gothoskar
Vicarious AI
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J. Swaroop Guntupalli
Vicarious AI
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Antoine Dedieu
Vicarious AI
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Miguel Lázaro-Gredilla
Vicarious AI
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Dileep George
Vicarious AI
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Abstract

Cognitive maps enable us to learn the layout of environments, encode and retrieve episodic memories, and navigate vicariously for mental evaluation of options. A unifying model of cognitive maps will need to explain how the maps can be learned scalably with sensory observations that are non-unique over multiple spatial locations (aliased), retrieved efficiently in the face of uncertainty, and form the fabric of efficient hierarchical planning. We propose learning higher-order graphs – structured in a specific way that allows efficient learning, hierarchy formation, and inference – as the general principle that connects these different desiderata. We show that these graphs can be learned efficiently from experienced sequences using a cloned Hidden Markov Model (CHMM), and uncertainty-aware planning can be achieved using message-passing inference. Using diverse experimental settings, we show that CHMMs can be used to explain the emergence of context-specific representations, formation of transferable structural knowledge, transitive inference, shortcut finding in novel spaces, remapping of place cells, and hierarchical planning. Structured higher-order graph learning and probabilistic inference might provide a simple unifying framework for understanding hippocampal function, and a pathway for relational abstractions in artificial intelligence.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted January 09, 2020.
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Learning cognitive maps for vicarious evaluation
Rajeev V. Rikhye, Nishad Gothoskar, J. Swaroop Guntupalli, Antoine Dedieu, Miguel Lázaro-Gredilla, Dileep George
bioRxiv 864421; doi: https://doi.org/10.1101/864421
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Learning cognitive maps for vicarious evaluation
Rajeev V. Rikhye, Nishad Gothoskar, J. Swaroop Guntupalli, Antoine Dedieu, Miguel Lázaro-Gredilla, Dileep George
bioRxiv 864421; doi: https://doi.org/10.1101/864421

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