Logic-based technologies for multi-agent systems: a systematic literature review

Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified 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....

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Veröffentlicht in:Autonomous agents and multi-agent systems Jg. 35; H. 1
Hauptverfasser: Calegari, Roberta, Ciatto, Giovanni, Mascardi, Viviana, Omicini, Andrea
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.04.2021
Springer Nature B.V
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ISSN:1387-2532, 1573-7454
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Abstract Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified 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 a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones.
AbstractList Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified 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 a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones.
Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified 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 a comprehensive view of those technologies by making them the subject of a systematic literature review (SLR). The resulting technologies are discussed and evaluated from two different perspectives: the MAS and the logic-based ones.
ArticleNumber 1
Author Omicini, Andrea
Calegari, Roberta
Ciatto, Giovanni
Mascardi, Viviana
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  orcidid: 0000-0003-3794-2942
  surname: Calegari
  fullname: Calegari, Roberta
  email: roberta.calegari@unibo.it
  organization: ALMA–AI Interdepartmental Center of Human Centered AI, Alma Mater Studiorum–Università di Bologna
– sequence: 2
  givenname: Giovanni
  orcidid: 0000-0002-1841-8996
  surname: Ciatto
  fullname: Ciatto, Giovanni
  organization: Dipartimento di Informatica – Scienza e Ingegneria (DISI), Alma Mater Studiorum–Università di Bologna
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  givenname: Viviana
  orcidid: 0000-0002-2261-9926
  surname: Mascardi
  fullname: Mascardi, Viviana
  organization: Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei Sistemi (DIBRIS), Università di Genova
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  givenname: Andrea
  orcidid: 0000-0002-6655-3869
  surname: Omicini
  fullname: Omicini, Andrea
  organization: Dipartimento di Informatica – Scienza e Ingegneria (DISI), Alma Mater Studiorum–Università di Bologna
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MAS
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Snippet Precisely when the success of artificial intelligence (AI) sub-symbolic techniques makes them be identified with the whole AI by many non-computer-scientists...
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SubjectTerms Agents (artificial intelligence)
Artificial Intelligence
Computer Science
Computer Systems Organization and Communication Networks
Current Trends in Research on Software Agents and Agent-Based Software Development
Intelligent systems
Literature reviews
Logic
Multiagent systems
Software Engineering/Programming and Operating Systems
Systematic review
User Interfaces and Human Computer Interaction
Title Logic-based technologies for multi-agent systems: a systematic literature review
URI https://link.springer.com/article/10.1007/s10458-020-09478-3
https://www.proquest.com/docview/2452108922
Volume 35
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