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Logic-based Technologies for Multi-agent Systems: A Systematic Literature Review

Roberta Calegari, Giovanni Ciatto, Viviana Mascardi, Andrea Omicini
Exactly when the success of artificial intelligence (AI) sub-simbolic techniques makes them be confused with the whole AI by many non-computer scientists and non-technical media, symbolic approaches are getting more and more attention as those that could make AI amenable to human understanding. Given the recurring cycles in the AI history, we expect that a revamp of technologies often tagged as “classical AI” – in particular, logic-based ones – will take place in the next few years. On the other hand, agents and multi-agent systems (MAS) have been at the core of the design of intelligent systems since their very beginning, and their long-term connection with logic-based technologies, which characterised their early days, might open new ways to engineer explainable intelligent systems. This is why understanding the current status of logic-based technologies for MAS is nowadays of paramount importance. Accordingly, this paper aims at providing an exhaustive view of such tech- nologies by presenting a carefully-designed and implemented systematic literature review (SLR). The standard SLR method has been followed, and the resulting technologies are discussed and evaluated from two different perspectives, the MAS and the logical ones.
Autonomous Agents and Multi-Agent Systems, 2019