BeeAI Framework provides a fully modular architecture for building intelligent agents that can perform tasks, manage state, and interact with external tools. It includes a memory manager for long-term context retention, a plugin system for custom skill integration, and built-in support for API chaining and multi-agent coordination. The framework offers Python and JavaScript SDKs, a command-line interface for scaffolding projects, and deployment scripts for cloud, Docker, or edge devices. Monitoring dashboards and logging utilities help track agent performance and troubleshoot issues in real time.

CommNet is a research-oriented library that implements the CommNet architecture, allowing multiple agents to share hidden states at each timestep and learn to coordinate actions in cooperative environments. It includes PyTorch model definitions, training and evaluation scripts, environment wrappers for OpenAI Gym, and utilities for customizing communication channels, agent counts, and network depths. Researchers and developers can use CommNet to prototype and benchmark inter-agent communication strategies on navigation, pursuit–evasion, and resource-collection tasks.

An AI Football Cup in a Java JADE Environment is an open-source demonstration that leverages the Java Agent DEvelopment Framework (JADE) to simulate a full soccer tournament. It models each player as an autonomous agent with behaviors for movement, ball control, passing, and shooting, coordinating via message passing to implement strategies. The simulator includes referee and coach agents, enforces game rules, and manages tournament brackets. Developers can extend decision-making with custom rules or integrate machine learning modules. This environment illustrates multi-agent communication, teamwork, and dynamic strategy planning within a real-time sports scenario.