Robust regulation adaptation in multi-agent systems

Adaptive 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 paper focuses on regulationadaptation 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 noncompliant agents. The evaluation is performed in a peer-to-peer sharing network scenario. Results show that our proposal signi?cantly increases system performance and can cope with regulation violators without incorporating any speci?c regulation-compliance enforcement mechanism. Source URL: https://www.iiia.csic.es/en/node/53940 Links [1] https://www.iiia.csic.es/en/bibliography?f[author]=164 [2] https://www.iiia.csic.es/en/staff/maite-l%C3%B3pez-s%C3%A1nchez [3] https://www.iiia.csic.es/en/bibliography?f[author]=165 [4] https://www.iiia.csic.es/en/bibliography?f[author]=166 [5] https://www.iiia.csic.es/en/staff/juan-rodr%C3%ADguez-aguilar