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multi-agent

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VectorizedMultiAgentSimulator

VMAS is a vectorized framework 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 Dec 12, 2023
  • Python

A completely private, locally-operated, highly customizable Ai Assistant/Chatbot/Sub-Agent Framework with realistic Long Term Memory and thought formation using Llama 2 or Open Ai's GPT. Qdrant is used for the Vector DB.

  • Updated Dec 6, 2023
  • Python

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