A Multi-Agent System for Industrial Fault Detection and Repair

Bevar, Vincenzo; Costantini, Stefania; Tocchio, Arianna; Gasperis, Giovanni De

doi:10.1007/978-3-642-28786-2_5

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…Primary references: [97] Other references describing / exploiting the technology: [36,98,99,101] URL: http://github.com/AAAI-DISIM-UnivAQ/DALI MAS perspective DALI is an agent programming language based on the active logic programming language [94] designed to make logical specifications of agents executable. A DALI agent is composed by reactive rules to face the events that can occur in the environment, as well as proactive rules, aimed at allowing the agent to perform actions on its own initiative.…”

Section: Dali (2002)mentioning

confidence: 99%

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

Calegari

Ciatto

Mascardi

et al. 2020

Auton Agent Multi-Agent Syst

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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.

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Section: Dali (2002)mentioning

confidence: 99%

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

Calegari

Ciatto

Mascardi

et al. 2020

Auton Agent Multi-Agent Syst

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show abstract

“…Although there has been some long running international forums, such as the International Conference on Practical Applications for Agents and Multi-agent Systems (PAAMS) and the Special Track in Innovative Applications in the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), most of the agent applications published so far are targeted for usages that not often actively involve the general public as direct stakeholders who actively interact with the technology [4], [5]. This is somehow not entirely the case for applications in the domain of education where personal interactions between the agents and learners frequently occur [6], [7].…”

Section: Introductionmentioning

confidence: 99%

From Internet of Things to Internet of Agents

Shen

Leung

2013

2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical A

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From sophisticated single agent in complex environments to multi-agent system (MAS) organizations, intelligent software agent research has come a long way in just under two decades. Many new branches of research in this field have emerged over the years which have enabled today's agents to perform a wide variety of human-like tasks such as learning, reasoning, negotiating, self-organizing and trusting each other, etc. Unfortunately, very few practical MASs have been deployed after such a long period of intensive research and development. For MASs to achieve higher popularity among end-users, we believe that agent oriented software engineering (AOSE) should adopt a new paradigm as has been done in Web 2.0 -to allow endusers to actively participate in developing or modifying features in agents at various stages of the agent's lifecycle. In this paper, we propose a vision for democratizing AOSE. We discuss what potential new researches need to be carried out in the areas of AOSE and agent learning in order to realize such a vision of moving from MASs to mass end-user agent development, and discuss potential challenges facing various aspects of this vision.

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“…In fact, each definite area of the building -e.g., the dining room, the bathroom, the hall, etc.-can be managed by a hybrid agent which plays the role of the prosumer, in communication with its siblings of the other areas, in order to accomplish the performance goals. Therefore, the energy management of the building can be represented in terms of a Multi-Agent Systems (MAS), where each agent deals with the others in terms of planning and forecasting, as in [2].…”

Section: Introductionmentioning

confidence: 99%

Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

Caianiello

Costantini

Gasperis

et al. 2013

Distributed Computing and Artificial Intelligence

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-We outline a solution to the problem of intelligent control of energy consumption of a smart building system by a prosumer planning agent that acts on the base of the knowledge of the system state and of a prediction of future states. Predictions are obtained by using a synthetic model of the system as obtained with a machine learning approach. We present case studies simulations implementing different instantiations of agents that control an air conditioner according to temperature set points dynamically chosen by the user. The agents are able of energy saving while trying to keep indoor temperature within a given comfort interval.

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A Multi-Agent System for Industrial Fault Detection and Repair

Cited by 5 publications

References 15 publications

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

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

From Internet of Things to Internet of Agents

Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

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