Adapting Autonomic Electronic Institutions to Heterogeneous Agent Societies

Authors:
Eva Bou;Maite López-Sánchez;J. A. Rodríguez-Aguilar;Jaime Simão Sichman
Affiliations:
IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Campus, Bellaterra, Spain UAB 08193;WAI, Volume Visualization and Artificial Intelligence, MAiA Dept., Universitat de Barcelona,;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish National Research Council, Campus, Bellaterra, Spain UAB 08193;LTI, Intelligent Techniques Laboratory, Computer Engineering Department, University of São Paulo, Brazil
Venue:
Organized Adaption in Multi-Agent Systems
Year:
2009

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Abstract

Electronic institutions (EIs) define the rules of the game in agent societies by fixing what agents are permitted and forbidden to do and under what circumstances. Autonomic Electronic Institutions (AEIs) adapt their rules to comply with their goals when regulating agent societies composed of varying populations of self-interested agents. We present a self-adaptation model based on Case-Based Reasoning (CBR) that allows an AEI to yield a dynamical answer to changing circumstances. In order to demonstrate adaptation empirically, we consider a traffic control scenario populated by heterogeneous agents. Within this setting, we demonstrate statistically that an AEI is able to adapt to different heterogeneous agent populations.