Chaos-based reinforcement learning with TD3

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.ai cs.lg cs.ne dynamics exploration exploratory learn reinforcement reinforcement learning type