RALE-ACL - A Language for Information Exchange between Case-Based Agents as Alternative to the FIPA-ACL-Based Communication

Viktor Eisenstadt, Klaus-Dieter Althoff

In: Roman Barták , Eric Bell (Hrsg.). Proceedings of the Thirty-Third International Florida Artificial Intelligence Research Society Conference. International FLAIRS Conference (FLAIRS-2020) May 17-20 Miami FL United States Seiten 185-188 AAAI Press 2020.


In this paper, we present RALE-ACL, a holistic communication architecture for case-based agents in multiagent systems (MAS) that employ case-based reasoning (CBR) as the main means of reasoning mechanism within their agents. RALE-ACL is an extension of RALE-CBR, a methodology for construction of CBR based approaches and systems that adds more flexibility to the classic 4R cycle of case-based reasoning. The main goal of RALE-ACL is to establish a much more CBR-compatible alternative to the KQML- and FIPAACL-based languages, that are currently used in many multi-agent systems, but are too generic and therefore only cumbersomely usable for the specific structure and purposes of case-based agents. This paper is the final part of the trilogy about the RALE methodology.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence