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Mava

Scalable Multi-Agent Reinforcement Learning in JAX with Advanced Parallel Processing

Product DescriptionThe project facilitates advanced research in multi-agent reinforcement learning using scalable JAX-based algorithms, enabling efficient parallel execution on various devices. It supports prominent MARL frameworks like CTDE and DTDE and includes adaptable environment wrappers for diverse tasks such as robotics and foraging. Mava ensures precise evaluation with comprehensive JSON logging, aiding in detailed analysis and performance optimization across different hardware environments. The open-source model supports community contributions and seamless integration into complex research workflows.
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