Best Response Shaping

arXiv:2404.06519v1 Announce Type: cross
Abstract: We investigate the challenge of multi-agent deep reinforcement learning in partially competitive environments, where traditional methods struggle to foster reciprocity-based cooperation. LOLA and POLA agents learn reciprocity-based cooperative policies by differentiation through a few look-ahead optimization steps of their opponent. However, there is a key limitation in these techniques. Because they consider a few optimization steps, a learning opponent that takes many steps to optimize its return may exploit them. In response, we introduce a …

abstract agent agents arxiv challenge cs.ai cs.gt cs.lg cs.ma differentiation environments however key learn lola look multi-agent optimization policies reinforcement reinforcement learning struggle through type