GenWorlds is an AI development framework designed to facilitate the creation of multi-agent systems. Utilizing an event-based communication framework via websocket, it allows developers to set up interactive environments where autonomous agents can asynchronously interact with each other and their surroundings. These agents collaborate, plan actions, and execute complex tasks collectively, making GenWorlds a robust platform for creating scalable and flexible AI ecosystems.

MultiAgentes provides a modular architecture for defining environments and agents, supporting synchronous and asynchronous multi-agent interactions. It includes base classes for environments and agents, predefined scenarios for cooperative and competitive tasks, tools for customizing reward functions, and APIs for agent communication and observation sharing. Visualization utilities allow real-time monitoring of agent behaviors, while logging modules record performance metrics for analysis. The framework integrates seamlessly with Gym-compatible reinforcement learning libraries, enabling users to train agents using existing algorithms. MultiAgentes is designed for extensibility, allowing developers to add new environment templates, agent types, and communication protocols to suit diverse research and educational use cases.