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Abstract. We consider a resource access control scenario in an open multi-agent system. We specify a mutable set of rules to determine how resource allocation is decided, and minimally assume agent behaviour with respect to these rules is either selfish or responsible. We then study how a combination of learning, reputation, and voting can be used, in the absence of any centralised enforcement mechanism, to ensure that it is more preferable to conform to a system norm than defect against it. This result indicates how it is possible to leverage local adaptation with respect to the Rules of Social-Exchange, Choice, and Order to promote a 'global' system property.

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Abstract. Coordination of agent teams depends on the scale of the team. Teams comprising hundreds of agents tend to perform better with local computation and interactions (i.e. swarm intelligence, evolutionary computing, etc.) Teams comprising tens of agents tend to perform better with more sophisticated agents (e.g. BDI agents) with complex reasoning abilities. In the long term, our objective is to achieve agent teams comprising hundreds of sophisticated agents: then, a key aspect of coordination and control is the idea of organised adaptation. In this paper we present a new multi-agent programming environment, PreSage-MS, a rapid prototyping and animation tool designed to facilitate experiments with organised adaptation in 'sophisticated' agent teams. We describe the system architecture and functionality, and give a walkthrough of experimental design. We conclude with a discussion of several issues, including the migration from design-time tools for human users to run-time services for software agents.

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