MARLlib: Extending RLlib for Multi-agent Reinforcement Learning. (arXiv:2210.13708v1 [cs.LG])

Despite the fast development of multi-agent reinforcement learning (MARL)
methods, there is a lack of commonly-acknowledged baseline implementation and
evaluation platforms. As a result, an urgent need for MARL researchers is to
develop an integrated library suite, similar to the role of RLlib in
single-agent RL, that delivers reliable MARL implementation and replicable
evaluation in various benchmarks. To fill such a research gap, in this paper,
we propose Multi-Agent RLlib (MARLlib), a comprehensive MARL algorithm library
that facilitates RLlib for …

arxiv reinforcement reinforcement learning rllib