scholarly journals On the Synergy between Virtual Reality and Multi-Agent Systems

2021 ◽  
Vol 13 (8) ◽  
pp. 4326
Author(s):  
Alejandra Ospina-Bohórquez ◽  
Sara Rodríguez-González ◽  
Diego Vergara-Rodríguez

Multi-agent systems integrate a great variety of artificial intelligence techniques from different fields, these systems have made it possible to create intelligent systems more efficiently. On the other hand, virtual reality applications are accepted as viable techniques in different areas such as visualization, simulation, design, and research. The combined use of these two technologies has led to the development of realistic and interactive applications. This work aims to do a Systematic Mapping Study (SMS) relying on the guidelines of Kitchenham and Petersen to analyze the state of the art of VR applications using multi-agent systems. Inclusion and exclusion criteria have been applied to identify relevant papers, 82 articles were selected and categorized according to the publication type, the research type, the asset type, and the purpose of the work. A complete review of the 82 selected articles was performed, based on the research questions that were established. This review made it possible to clarify the open lines of research that exist and to know where research in this field can be directed.

2021 ◽  
Vol 17 (3) ◽  
pp. 88-99
Author(s):  
Roderic A. Girle

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.


2021 ◽  
Vol 2094 (3) ◽  
pp. 032033
Author(s):  
I A Kirikov ◽  
S V Listopad ◽  
A S Luchko

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.


2020 ◽  
Vol 35 (1) ◽  
Author(s):  
Roberta Calegari ◽  
Giovanni Ciatto ◽  
Viviana Mascardi ◽  
Andrea Omicini

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.


Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 363 ◽  
Author(s):  
Davide Calvaresi ◽  
Jean-Paul Calbimonte ◽  
Alevtina Dubovitskaya ◽  
Valerio Mattioli ◽  
Jean-Gabriel Piguet ◽  
...  

The agent based approach is a well established methodology to model distributed intelligent systems. Multi-Agent Systems (MAS) are increasingly employed in applications dealing with safety and information critical tasks (e.g., in eHealth, financial, and energy domains). Therefore, transparency and the trustworthiness of the agents and their behaviors must be enforced. For example, employing reputation based mechanisms can promote the development of trust. Nevertheless, besides recent early stage studies, the existing methods and systems are still unable to guarantee the desired accountability and transparency adequately. In line with the recent trends, we advocate that combining blockchain technology (BCT) and MAS can achieve the distribution of the trust, removing the need for trusted third parties (TTP), potential single points of failure. This paper elaborates on the notions of trust, BCT, MAS, and their integration. Furthermore, to attain a trusted environment, this manuscript details the design and implementation of a system reconciling MAS (based on the Java Agent DEvelopment Framework (JADE)) and BTC (based on Hyperledger Fabric). In particular, the agents’ interactions, computation, tracking the reputation, and possible policies for disagreement-management are implemented via smart contracts and stored on an immutable distributed ledger. The results obtained by the presented system and similar solutions are also discussed. Finally, ethical implications (i.e., opportunities and challenges) are elaborated before concluding the paper.


2021 ◽  
Vol 35 (1) ◽  
Author(s):  
Davide Calvaresi ◽  
Yashin Dicente Cid ◽  
Mauro Marinoni ◽  
Aldo Franco Dragoni ◽  
Amro Najjar ◽  
...  

AbstractSince its dawn as a discipline, Artificial Intelligence (AI) has focused on mimicking the human mental processes. As AI applications matured, the interest for employing them into real-world complex systems (i.e., coupling AI with Cyber-Physical Systems—CPS) kept increasing. In the last decades, the multi-agent systems (MAS) paradigm has been among the most relevant approaches fostering the development of intelligent systems. In numerous scenarios, MAS boosted distributed autonomous reasoning and behaviors. However, many real-world applications (e.g., CPS) demand the respect of strict timing constraints. Unfortunately, current AI/MAS theories and applications only reason “about time” and are incapable of acting “in time” guaranteeing any timing predictability. This paper analyzes the MAS compliance with strict timing constraints (real-time compliance)—crucial for safety-critical applications such as healthcare, industry 4.0, and automotive. Moreover, it elicits the main reasons for the lack of real-time satisfiability in MAS (originated from current theories, standards, and implementations). In particular, traditional internal agent schedulers (general-purpose-like), communication middlewares, and negotiation protocols have been identified as co-factors inhibiting real-time compliance. To pave the road towards reliable and predictable MAS, this paper postulates a formal definition and mathematical model of real-time multi-agent systems (RT-MAS). Furthermore, this paper presents the results obtained by testing the dynamics characterizing the RT-MAS model within the simulator MAXIM-GPRT. Thus, it has been possible to analyze the deadline miss ratio between the algorithms employed in the most popular frameworks and the proposed ones. Finally, discussing the obtained results, the ongoing and future steps are outlined.


2021 ◽  
pp. 32-42
Author(s):  
Alejandra Ospina-Bohórquez ◽  
Sara Rodríguez-González ◽  
Diego Vergara-Rodríguez

2020 ◽  
Author(s):  
Diego Fernando Andaluz Espinosa ◽  
Patricio Alejandro Molina Palma ◽  
José Rubén Caiza Caizabuano

Multi-agent systems have gained a lot of interest in articles, conferences and magazines. However, it is still a recent issue which is not understood or the scope of it is unknown. The objective of this work is to investigate in more detail the articles and to build a preliminary classification system to structure the field of Multi-agent systems. As a result, an overview of this area of research can be obtained through the response to the research questions posed. Resumen. Los sistemas multi-agente han ganado un interés muy grande en artículos, conferencias y revistas. Sin embargo sigue siendo un tema reciente el cual no se comprende ni se conoce los alcances del mismo. Este trabajo tiene como objetivo investigar con más detalle los artículos y construir un sistema de clasificación preliminar para estructurar el campo de los sistemas Multi-agente. Como resultado, se espera proporcionar una visión general de esta área de investigación a través de responder a las preguntas de investigación planteadas. Creemos que el presente trabajo será una herramienta que encontrará ámbitos todavía aun no investigados.


2012 ◽  
Vol 21 (03) ◽  
pp. 1202002
Author(s):  
ZHIHUA CUI ◽  
ZHONGZHI SHI ◽  
RAJAN ALEX

Swarm intelligence is an umbrella for amount optimization algorithms. This discipline deals with natural and artificial systems composed of many individuals that coordinate their activities using decentralized control and self-organization. In general, multi-agent systems that use some swarm intelligence are said to be swarm intelligent systems. They are mostly used as search engines and optimization tools. The goal of this special issue has been to offer a wide spectrum of sample works throughout the world about innovative methodologies of swarm intelligence. The issue should be useful both for beginners and experienced researchers in the field of computational intelligence.


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