A2A4J is a lightweight Java framework designed for building autonomous AI agents. It offers abstractions for agents, tools, memories, and planners, supporting asynchronous execution of tasks and seamless integration with OpenAI and other LLM APIs. Its modular design lets you define custom tools and memory stores, orchestrate multi-step workflows, and manage decision loops. With built-in error handling, logging, and extensibility, A2A4J accelerates the development of intelligent Java applications and microservices.

CArtAgO (Common ARTifact Infrastructure for AGents Open environments) is a lightweight, extensible framework for implementing environment infrastructures in multi-agent systems. It introduces the concept of artifacts: first-class entities representing environment resources with defined operations, observable properties, and event interfaces. Developers define artifact types in Java, register them in environment classes, and expose operations and events for agent consumption. Agents interact with artifacts using standard actions (e.g., createArtifact, observe), receive asynchronous notifications of state changes, and coordinate through shared resources. CArtAgO integrates easily with agent platforms such as Jason, JaCaMo, JADE, and Spring Agent, enabling hybrid system development. The framework provides built-in support for artifact documentation, dynamic loading, and runtime monitoring, facilitating rapid prototyping of complex agent-based applications.

Java-Action-Bool integrates seamlessly with the LightJason multi-agent framework, enabling developers to leverage ready-made boolean logic actions in their agent programs. Instead of writing custom boolean checks, you can call provided actions like ActionBoolAnd, ActionBoolOr, ActionBoolNot, and more. These actions evaluate truth values at runtime to guide agent behavior, reducing boilerplate code and simplifying plan definitions in cognitive and reactive agent systems.