Experiments on robustness and deception in a coalition formation model

In the last few years coalition formation algorithms have been proposed as a possible way of modeling autonomous agent cooperation in multi-agent systems. This work is based on a previously proposed coalition formation model founded on game theory for a class of task-oriented problems that guarantees an optimum task allocation and a stable profit division. In this paper we study two properties of the model that are very important for application in real-life scenarios: robustness and tolerance to an agent's misbehavior. First, we study the robustness of this model as regards the effect the agent's failure has on the resultant profits of the coalition formation. Secondly, we also study the coalition formation model in the presence of misbehaving agents. Agents have some kind of execution autonomy, and they can deceive or mislead each other when they reveal their information, if they believe this will give them more profits. Copyright (c) 2005 John Wiley & Sons, Ltd.