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Título

Robust regulation adaptation in multi-agent systems

AutorCampos, Jordi; López-Sánchez, Maite ; Salamó, Maria; Avila, Pedro; Rodríguez-Aguilar, Juan Antonio
Palabras claveOrganisation
Case-based
Regulation
Reasoning
Adaptation
Machine
Learning
Centred MAS
Fecha de publicación2013
EditorAssociation for Computing Machinery
CitaciónACM Transactions on Autonomous and Adaptive Systems 8 (3), 2013
ResumenAdaptive organisation-centred multi-agent systems can dynamically modify their organisational components to better accomplish their goals. Our research line proposes an abstract distributed architecture (2- LAMA) to endow an organisation with adaptation capabilities. This article focuses on regulation-adaptation based on a machine learning approach, in which adaptation is learned by applying a tailored case-based reasoning method. We evaluate the robustness of the system when it is populated by non compliant agents. The evaluation is performed in a peer-to-peer sharing network scenario. Results show that our proposal significantly improves system performance and can cope with regulation violators without incorporating any specific regulation-compliance enforcement mechanisms. © 2013 ACM.
URIhttp://hdl.handle.net/10261/133778
DOI10.1145/2517328
Identificadoresdoi: 10.1145/2517328
issn: 1556-4665
Aparece en las colecciones: (IIIA) Artículos
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