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What is Cogment?
Cogment is an open-source platform designed to address the challenges of continuous training of humans and AI together. It enables the creation, training, and operation of AI agents within simulated or real-world environments, fostering collaboration between humans and AI.
The platform supports a modular approach, reducing computational usage and facilitating validation. Cogment allows for a smooth transition from simulation to real-world deployment, promoting safe and efficient training.
Features
- Multi-actor: Allow multiple agents and human users to interact within the same environment.
- Multi-method: Train agents using various methods like Reinforcement Learning, Imitation Learning, and Curriculum Learning.
- Tech stack agnostic: Develop components using different tech stacks (Pytorch, Keras, Tensorflow, Unity, OpenAI Gym, etc.).
- Multi-experience learning: Run multiple instances of agents in distributed trials.
- Implementation swapping: Swap actors between different agent implementations, human users, or trained/untrained agents.
- Multi-source and retroactive rewards: Multiple RL agents can utilize various reward sources and handle delayed evaluations.
- Hybrid AI: Combine different agent types (expert systems, planners, neural networks, etc.).
- Optimized for minimal discontinuity between development and deployment: Iterative development with seamless transition between simulated and real environments.
Use Cases
- Training AI agents in collaborative or competitive scenarios.
- Developing AI systems that require human-in-the-loop learning.
- Creating simulations for complex systems involving human and AI interaction.
- Building hybrid AI systems that combine different AI approaches.
- Orchestrating intelligence ecosystems with the best of human and AI capabilities.
- Progressive deployment from simulated training environment to real environment.
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