A Meta-Agent Based Approach to Exploit the Collective Product of Mobile Cyber-Physical Collectives

Khenifar, Afra and Jamont, Jean-Paul and Occello, Michel and Ben-Yelles, Choukri-Bey and Koudil, Mouloud (2022) A Meta-Agent Based Approach to Exploit the Collective Product of Mobile Cyber-Physical Collectives. Frontiers in Robotics and AI, 9. ISSN 2296-9144

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Abstract

A cyber-physical system (CPS) is a system with integrated computational and physical abilities. Deriving the notion of cyber-physical collective (CPC) from a social view of CPS, we consider the nodes of a CPS as individuals (agents) that interact to overcome their limits in the collective. When CPC agents are able to move in their environment, the CPC is considered as a Mobile CPC (MCPC). The interactions of the agents give rise to the appearance of a phenomenon collectively generated by the agents of the CPC that we call a collective product. This phenomenon is not recorded as “a whole” in the CPC because an agent has only a partial view of its environment. This paper presents COPE (COllective Product Exploitation), an approach that allows one MCPC to exploit the collective product of another one. The approach is based on the deployment of meta-agents in both systems. A meta-agent is an agent that is external to a MCPC but is associated with one of its agents. Each meta-agent is able to monitor the agent with which it is associated and can fake its perceptions to influence its behavior. The meta-agents deployed in the system from which the collective product emerges provide indicators related to this product. Utilizing these indicators, the meta-agents deployed in the other system can act on the agents in order to adapt the global dynamics of the whole system. The proposed coupling approach is evaluated in a “fire detection and control” use case. It allows a system of UAVs to use the collective product of a network of sensors to monitor the fire.

Item Type: Article
Subjects: OA Open Library > Mathematical Science
Depositing User: Unnamed user with email support@oaopenlibrary.com
Date Deposited: 22 Jun 2023 07:06
Last Modified: 17 Nov 2023 03:50
URI: http://archive.sdpublishers.com/id/eprint/1124

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