Cogment

Cogment is an open-source platform developed by AI Redefined to facilitate the shared training of humans and AI within dynamic environments. It specializes in human-in-the-loop learning (HILL) and multi-agent reinforcement learning (MARL), allowing researchers and developers to scale their AI's training and validation processes. Cogment Versatility is its unique feature, leveraging adaptability across varied tech stacks and training methodologies. Users can employ a mix of expert systems, neural networks, and various frameworks like Pytorch, Keras, and Tensorflow in digital twin simulations and real-world applications.

Cogment supports heterogeneous agents and human actors in collaborative or competitive settings. With capabilities for managing multiple agents, agents can train using strategies such as reinforcement, imitation, and curriculum learning. Its seamless integration permits swapping actors between humans and AI agents, boosting the bootstrap phase with pseudo-humans or rule-based agents. A focus on centralized as well as decentralized training schemes allows for both individual and mass specialization of agent populations.

This platform not only aims for efficient training but also ensures quick iteration cycles between simulated and real environments, promoting iterative development without differentiation between developed and production-ready versions.