May 16, 2024, 4:41 a.m. | Toshitaka Matsuki, Yusuke Sakemi, Kazuyuki Aihara

cs.LG updates on

arXiv:2405.09086v1 Announce Type: new
Abstract: Chaos-based reinforcement learning (CBRL) is a method in which the agent's internal chaotic dynamics drives exploration. This approach offers a model for considering how the biological brain can create variability in its behavior and learn in an exploratory manner. At the same time, it is a learning model that has the ability to automatically switch between exploration and exploitation modes and the potential to realize higher explorations that reflect what it has learned so far. …

abstract agent arxiv behavior brain chaos create cs.lg dynamics exploration exploratory learn reinforcement reinforcement learning type

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