A negotiation platform for cooperating multi-agent systems

Research in Distributed Artificial Intelligence attempts to integrate and coordinate the activities of multiple, intelligent problem solvers that interact to solve complex tasks in domains such as design, medical diagnosis, business management, and so on. Due to the different goals, knowledge and viewpoints of the agents, conflicts might arise at any phase of the problem-solving process. Managing diverse knowledge requires well-organized models of conflict resolution. In this thesis, a computational model for cooperating intelligent agents which openly supports multi-agent conflict detection and resolution is described. The model is based on the insights that each agent has its own conflict management knowledge which is separated from its domain level knowledge. Each agent has its own conflict management knowledge which is not accessible or visible to others. Furthermore, there are no globally known conflict resolution strategies. Each agent involved in a conflict chooses a resolution scheme according to its self-interest. The problem-solving environment allows a new problem solver to be added or an existing one to be removed, without requiring any modification of the rest of the model, and therefore achieves open information system semantics.