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multi-agent-systems

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VectorizedMultiAgentSimulator

VMAS is a vectorized differentiable simulator designed for efficient Multi-Agent Reinforcement Learning benchmarking. It is comprised of a vectorized 2D physics engine written in PyTorch and a set of challenging multi-robot scenarios. Additional scenarios can be implemented through a simple and modular interface.

  • Updated Jul 1, 2024
  • Python

ML.GUIDE is a Multi-LLM Agent System designed to help professionals define, evaluate, and solve machine learning problems. It leverages specialized AI agents for tasks like problem definition, data assessment, model recommendations, research, and code generation. Developed in 17 hours during the AI National Summit (AINS) hackathon on June 9, 2024.

  • Updated Jun 21, 2024
  • Python

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