Mava: a research library for distributed multi-agent reinforcement learning in JAX

Understand

Multi-agent reinforcement learning (MARL) research is inherently computationally expensive and it is often difficult to obtain a sufficient number of experiment samples to test hypotheses and make robust statistical claims.

• Furthermore, MARL algorithms are typically complex in their design and can be tricky to implement correctly.
• These aspects of MARL present a difficult challenge when it comes to creating useful software for advanced research.
• Our criteria for such software is that it should be simple enough to use to implement new ideas quickly, while at the same time be scalable and fast enough to test those ideas in a reasonable amount of time.