Multi-Agent Reinforcement Learning
This section covers the core concepts, methodologies, and representative algorithms of Multi-Agent Reinforcement Learning (MARL).
Contents
| Topic | Description |
|---|---|
| MARL Survey | Core challenges, paradigm taxonomy, and problem formulations in MARL |
| MARL Algorithms | Value decomposition, multi-agent policy gradient, communication mechanisms, classic case studies |
Recommended Reading Order
- Start with MARL Survey to understand problem definitions and methodological frameworks
- Then read MARL Algorithms for a deep dive into representative algorithms
Related Sections
- RL Landscape — Global view of RL methodology
- PPO Algorithm — Foundation for MAPPO
- TD3 and DDPG — Foundation for MADDPG