Allocating tasks in extreme teams
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Monotonic concession protocols for multilateral negotiation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Multi-agent role allocation: issues, approaches, and multiple perspectives
Autonomous Agents and Multi-Agent Systems
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An important issue in many multiagent systems is the way in which agents can be coordinated in order to perform different roles. This paper proposes a method by which the agents can self-organize based on the changes of their individual utilities. We assume that the tasks given to the agents have a number of attributes and complexity levels, and that the agents have different preferences regarding these features. The adaptive behaviour of the agents is based on the psychological theory of cognitive dissonance, where an agent working on a low-preference task gradually improves its attitude towards it. The agents go through personal learning curves and improve their performance by learning or decrease it by forgetting. A (near-) optimal assignment of tasks between agents is achieved by an evolutionary multilateral negotiation, as agents value the attributes of the tasks differently. Over repeated trials, the system is shown to stabilize, and the agents converge to specific roles, i.e. handling tasks mainly defined by particular attributes. The total productivity of the system increases as an emergent property of the system.