Angerona - A flexible multiagent framework for knowledge-based agents

Abstract

We present the Angerona framework for the implementation of knowledge-based agents with a strong focus on flexibility, extensibility, and compatibility with diverse knowledge representation formalisms. As the basis for this framework we propose and formalize a general concept of compound agents in which we consider agents to consist of hierarchies of interacting epistemic and functional components. Each epistemic component is instantiated by a knowledge representation formalism. Different knowledge representation formalisms can be used within one agent and different agents in the same system can be based on different agent architectures and can use different knowledge representation formalisms. Partially instantiations define sub-frameworks for, e. g., the development of BDI agents and variants thereof. The Angerona framework realizes this concept by means of a flexible JAVA plug-in architecture for the epistemic and the functional components of an agent. The epistemic plug-ins are based on the Tweety library for knowledge representation, which provides various ready-for-use implementations and knowledge representation formalisms and a framework for the implementation of additional ones. Angerona already contains several partial and complete instantiations that implement several approaches. Angerona also features an environment plug-in for communicating agents and a flexible GUI to monitor the multiagent system and the inner workings of the agents, particularly the inspection of the dynamics of their epistemic states. Angerona and Tweety are ready to use, well documented, and open source.