Nagato AI is an extensible AI agent framework that orchestrates autonomous workflows by combining task planning, memory management, and tool integrations. Users can define custom tools and APIs, allowing the agent to retrieve information, perform actions, and maintain conversational context over long sessions. With its plugin architecture and conversational UI, Nagato AI adapts to diverse scenarios—from research assistance and data analysis to personal productivity and automated customer interactions—while remaining fully open-source and developer-friendly.

SARL isms for decision-making and supports the dynamic with the Eclipse IDE, offering editor support, code generation, debugging, and testing tools. The runtime engine can target various platforms, including simulation frameworks (e.g., MadKit, Janus) and real-world systems in robotics and IoT. Developers can structure complex MAS applications by assembling modular skills and protocols, simplifying the development of adaptive, distributed AI systems.

ASP-DALI provides a unified platform for defining and executing logic-based intelligent agents. Developers write ASP rules to represent agent knowledge and goals, while DALI constructs define event reactions and action executions. At runtime, an ASP solver computes answer sets that guide the agent’s decisions, enabling it to plan, react to incoming events, and adjust beliefs dynamically. The framework supports modular knowledge bases, facilitating incremental updates and clear separation between declarative rules and reactive behaviors. ASP-DALI is implemented in Prolog with interfaces to popular ASP solvers, simplifying integration and deployment across research and prototype scenarios.