A scalable reinforcement learning framework inspired by hippocampal memory mechanisms for efficient contextual and sequential decision making

A scalable reinforcement learning framework inspired by hippocampal memory mechanisms for efficient contextual and sequential decision making

Abstract Efficient decision-making in context-dependent, sequential tasks remains a fundamental challenge in reinforcement learning (RL). Inspired by the function of the brain’s hippocampal system, we introduce Hippocampal-Augmented Memory Integration (HAMI), a biologically inspired memory-based RL...

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Main Authors: Hamed Poursiami, Ayana Moshruba, Keiland W. Cooper, Derek Gobin, Md Abdullah-Al Kaiser, Ankur Singh, Rouhan Noor, Babak Shahbaba, Akhilesh Jaiswal, Norbert J. Fortin, Maryam Parsa
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-10586-x
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https://doi.org/10.1038/s41598-025-10586-x

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