In this paper we present J-ALINAs, a JADE-based Architecture for LINguistic Agents. The purpose of this architecture is to support communication between agents whose beliefs and intentions are driven by different, heterogeneous, knowledge models. This objective, often referred in literature as semantic coordination, can be carried on through the identification of specific agent roles and behaviors dedicated to the mediation of agents' knowledge. In particular, such minimal hypotheses suggest an intelligent exploitation of natural language based technologies (resources and systems) as a necessary choice for capturing those similarities between the different knowledge models of agents trying to communicate, which are not in any way formally ratified. We aim to provide a flexible framework to be adopted in open multi-agent environments across different scenarios, providing a further abstraction level from the underlying details related to specific semantic coordination approaches; a high-cohesion and low-coupling design, and an agent-interaction protocol make possible for the architecture to face non-ideal use cases optimizing the communications among the agents. We discuss significant design issues, provide a prototypical implementation based on the JADE platform and a case study - MAPLE - integrating an ontology mapping component in the framework, showing flexibility of the architecture in real applications and its independence from any specific mapping algorithm. Finally we will look at the semantic coordination protocol we designed from a strictly formal perspective, providing a CCS (Milner's Calculus for Communicating Systems) description of the protocol itself.
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