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

2020 ◽  
Vol 35 (1) ◽  
Author(s):  
Roberta Calegari ◽  
Giovanni Ciatto ◽  
Viviana Mascardi ◽  
Andrea Omicini
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
Intelligent Systems ◽  
Current Status ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Computer Scientists ◽  
Multi Agent ◽  
The Subject

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.

Agent mining approaches: an ontological view

2021 ◽  
Vol 36 ◽  
Author(s):  
Emmanuelle Grislin-Le Strugeon ◽  
Kathia Marcal de Oliveira ◽  
Dorsaf Zekri ◽  
Marie Thilliez
Keyword(s):  
Data Mining ◽  
Literature Review ◽  
Knowledge Discovery ◽  
Systematic Literature Review ◽  
Software Agent ◽  
Application Domain ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Agent Mining ◽  
Multi Agent

Abstract Introduced as an interdisciplinary area that combines multi-agent systems, data mining and knowledge discovery, agent mining is currently in practice. To develop agent mining applications involves a combination of different approaches (model, architecture, technique and so on) from software agent and data mining (DM) areas. This paper presents an investigation of the approaches used in the agent mining systems by deeply analyzing 121 papers resulting from a systematic literature review. An ontology was defined to capitalize the knowledge collected from this study. The ontology is organized according to seven main facets: the problem addressed, the application domain, the agent-related and the mining-related elements, the models, processes and algorithms. This ontology is aimed at providing support to decisions about agent mining application design.

Foundations for Knowledge and Belief Management

2021 ◽  
Vol 17 (3) ◽  
pp. 88-99
Author(s):  
Roderic A. Girle
Keyword(s):  
Intelligent Systems ◽  
Turing Test ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Conceptual Structures ◽  
Interacting Agents ◽  
Questions And Answers ◽  
Multi Agent ◽  
The Difference ◽  
Dialogue Theory

Three foundational principles are introduced: intelligent systems such as those that would pass the Turing test should display multi-agent or interactional intelligence; multi-agent systems should be based on conceptual structures common to all interacting agents, machine and human; and multi-agent systems should have an underlying interactional logic such as dialogue logic. In particular, a multi-agent rather than an orthodox analysis of the key concepts of knowledge and belief is discussed. The contrast that matters is the difference between the different questions and answers about the support for claims to know and claims to believe. A simple multi-agent system based on dialogue theory which provides for such a difference is set out.

scholarly journals Agents’ ontologies negotiation in cohesive hybrid intelligent multi-agent systems

2021 ◽  
Vol 2094 (3) ◽  
pp. 032033
Author(s):  
I A Kirikov ◽  
S V Listopad ◽  
A S Luchko
Keyword(s):  
Intelligent Agents ◽  
Intelligent Systems ◽  
Multi Agent Systems ◽  
Labor Costs ◽  
Joint Work ◽  
Working Process ◽  
Agent Systems ◽  
Development Teams ◽  
Multi Agent ◽  
Domain Models

Abstract The paper proposes the model for negotiating intelligent agents’ ontologies in cohesive hybrid intelligent multi-agent systems. Intelligent agent in this study will be called relatively autonomous software entity with developed domain models and goal-setting mechanisms. When such agents have to work together within single hybrid intelligent multi-agent systems to solve some problem, the working process “go wild”, if there are significant differences between the agents’ “points of view” on the domain, goals and rules of joint work. In this regard, in order to reduce labor costs for integrating intelligent agents into a single system, the concept of cohesive hybrid intelligent multi-agent systems was proposed that implement mechanisms for negotiating goals, domain models and building a protocol for solving the problems posed. The presence of these mechanisms is especially important when building intelligent systems from intelligent agents created by various independent development teams.

A multidisciplinary perspective on multi-agent systems

2000 ◽  
Vol 15 (3) ◽  
pp. 293-301
Author(s):  
EDMUND CHATTOE ◽  
KERSTIN DAUTENHAHN ◽  
IAN DICKINSON ◽  
JIM DORAN ◽  
NIR VULKAN
Keyword(s):  
Artificial Agent ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Engineering Discipline ◽  
Key Points ◽  
Computer Scientists ◽  
Multi Agent ◽  
Multidisciplinary Perspective ◽  
Computational Systems

The theory, principles and practice of multi-agent systems is typically characterised as a computational and engineering discipline, since it is through the medium of computational systems that artificial agent systems are most commonly expressed. However, most definitions of agency draw directly on non-computational disciplines for inspiration. During the 1999 UK workshop on multi-agent systems, UKMAS'99, we invited four speakers to address the conceptualisation of multi-agent systems from their perspective as non-computer scientists. This paper presents their arguments and summarises some of the key points of discussion during the panel.

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