Allocation Algorithms in Dynamic Negotiation-Based Coalition Formation

In this paper, we present a set of allocation algorithms for a dynamic, negotiation-based coalition formation model. The model is for a cooperative multiagent system in which each agent has incomplete information about its dynamic and uncertain world and must respond to sensed events within time constraints. With incomplete information and uncertain world parameters while lacking time, an agent cannot afford organizing a rationally optimal coalition formation. Instead, our agents use a two-stage methodology. When an agent detects an event in the world, it first compiles a list of coalition candidates that it thinks would be useful, and then negotiates with the candidates. A negotiation is an exchange of information and knowledge for constraint satisfaction until both parties agree on a deal or one opts out. Each successful negotiation adds a new member to the agent’s final coalition. The agent that initiates the coalition needs to determine the task distribution among the members of the coalition and designs its coalition strategy to increase the chance of successfully forming a working coalition. Since the environment is dynamic, noisy, and the agents are resource-constrained, agents must form the working coalition to react to events as soon as possible and with whatever partial information they currently hold. Thus, the allocation algorithms have to take these constraints into account.