Multi-Agent Systems is designed to simplify the creation, configuration, and execution of distributed agent-based architectures. Developers can define agent behaviors, communication ontologies, and service descriptions within Java classes. The framework handles container setup, message transport, and life-cycle management for agents. Built on standard FIPA protocols, it supports peer-to-peer negotiation, collaborative planning, and modular extension. Users can run, monitor, and debug multi-agent scenarios on a single machine or across networked hosts, making it ideal for research, education, and small-scale deployments.

CybMASDE enables researchers and developers to build, configure, and execute multi-agent simulations with deep reinforcement learning. Users can author custom scenarios, define agent roles and reward functions, and plug in standard or custom RL algorithms. The framework includes environment servers, networked agent interfaces, data collectors, and rendering utilities. It supports parallel training, real-time monitoring, and model checkpointing. CybMASDE’s modular architecture allows seamless integration of new agents, observation spaces, and training strategies, accelerating experimentation in cooperative control, swarm behavior, resource allocation, and other multi-agent use cases.