HMAS is an open-source Python framework that enables development of hierarchical multi-agent systems. It offers abstractions for defining agent hierarchies, inter-agent communication protocols, environment integration, and built-in training loops. Researchers and developers can use HMAS to prototype complex multi-agent interactions, train coordinated policies, and evaluate performance in simulated environments. Its modular design makes it easy to extend and customize agents, environments, and training strategies.

JasonEnvironments delivers a collection of environment modules designed specifically for the Jason multi-agent system. Each module exposes a standardized interface so agents can perceive, act, and interact within diverse scenarios like pursuit-evasion, resource foraging, and cooperative tasks. The library is easy to integrate into existing Jason projects: just include the JAR, configure the desired environment in your agent architecture file, and launch the simulation. Developers can also extend or customize parameters and rules to tailor the environment to their research or educational needs.