Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization.
Wenqi ZhangKe TangHai WuMengna WangYongliang ShenGuiyang HouZeqi TanPeng LiYueting ZhuangWeiming LuPublished in: CoRR (2024)
Keyphrases
- learning process
- learning algorithm
- reinforcement learning
- action selection
- multi agent systems
- prior knowledge
- multi agent
- active learning
- supervised learning
- dynamic environments
- learning capabilities
- inverse reinforcement learning
- state action
- partially observable
- agent technology
- agent architecture
- optimization algorithm
- higher level
- access control
- optimization problems