Independent Generative Adversarial Self-Imitation Learning in Cooperative Multiagent Systems

Understand

Many tasks in practice require the collaboration of multiple agents through reinforcement learning.

• In general, cooperative multiagent reinforcement learning algorithms can be classified into two paradigms: Joint Action Learners (JALs) and Independent Learners (ILs).
• In many practical applications, agents are unable to observe other agents' actions and rewards, making JALs inapplicable.
• In this work, we focus on independent learning paradigm in which each agent makes decisions based on its local observations only.