multi_agent_celar

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multi_agent_celar provides researchers and developers with an open-source framework for training and evaluating multiple AI agents that learn to communicate via emergent language protocols. It features customizable environments, configurable agent policies, and tools for monitoring collaboration metrics in simulation.
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May 03 2025
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multi_agent_celar

multi_agent_celar

0
0
multi_agent_celar
multi_agent_celar provides researchers and developers with an open-source framework for training and evaluating multiple AI agents that learn to communicate via emergent language protocols. It features customizable environments, configurable agent policies, and tools for monitoring collaboration metrics in simulation.
Added on:
Social & Email:
Platform:
May 03 2025
--
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What is multi_agent_celar?

multi_agent_celar is designed as a modular AI platform enabling emergent-language communication among multiple intelligent agents in simulated environments. Users can define agent behaviors via policy files, configure environment parameters, and launch coordinated training sessions where agents evolve their own communication protocols to solve cooperative tasks. The framework includes evaluation scripts, visualization tools, and support for scalable experiments, making it ideal for research on multi-agent collaboration, emergent language, and decision-making processes.

Who will use multi_agent_celar?

  • AI researchers
  • Machine learning engineers
  • Academic educators
  • Graduate students

How to use the multi_agent_celar?

  • Step1: Clone the repository from GitHub.
  • Step2: Install required dependencies via pip install -r requirements.txt.
  • Step3: Configure agents and environment settings in config.yaml.
  • Step4: Run training scripts (python train.py) to start multi-agent simulation.
  • Step5: Monitor emergent communication using provided logging tools.
  • Step6: Customize or extend agent policies and environments as needed.

Platform

  • mac
  • windows
  • linux

multi_agent_celar's Core Features & Benefits

The Core Features

  • Emergent language communication protocols
  • Multi-agent environment simulation
  • Configurable agent policies
  • Training and evaluation scripts
  • Visualization and logging tools

The Benefits

  • Accelerates multi-agent research prototyping
  • Modular and extensible design
  • Open-source community collaboration
  • Reproducible training experiments

multi_agent_celar's Main Use Cases & Applications

  • Academic research on multi-agent collaboration
  • Benchmarking emergent communication protocols
  • Educational demonstrations in AI courses
  • Prototyping cooperative AI systems

FAQs of multi_agent_celar

multi_agent_celar Company Information

multi_agent_celar Reviews

5/5
Do You Recommend multi_agent_celar? Leave a Comment Below!

multi_agent_celar's Main Competitors and alternatives?

  • PettingZoo
  • OpenAI Gym Multi-Agent
  • Ray RLlib
  • MAgent

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