Using cost-aware transitions for reorganizing multiagent systems
Engineering Applications of Artificial Intelligence
Persuading agents to act in the right way: An incentive-based approach
Engineering Applications of Artificial Intelligence
Robust Regulation Adaptation in Multi-Agent Systems
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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Organisations in multi-agent systems (MAS) have proven to be successful in regulating agent societies. Nevertheless, changes in agents’ behaviour or in the dynamics of the environment may lead to a poor fulfilment of the system’s purposes, and so the entire organisation needs to be adapted. In this paper we focus on endowing the organisation with adaptation capabilities, instead of expecting agents to be capable of adapting the organisation by themselves. We regard this organisational adaptation as an assisting service provided by what we call the Assistance Layer. Our generic Two Level Assisted MAS Architecture (2-LAMA) incorporates such a layer. We empirically evaluate this approach by means of an agent-based simulator we have developed for the P2P sharing network domain. This simulator implements 2-LAMA architecture and supports the comparison between different adaptation methods, as well as, with the standard BitTorrent protocol. In particular, we present two alternatives to perform norm adaptation and one method to adapt agents’ relationships. The results show improved performance and demonstrate that the cost of introducing an additional layer in charge of the system’s adaptation is lower than its benefits.