A distributed algorithm for agent coalition formation with complex tasks

Forming coalitions for a group of tasks efficiently in a distributed setting is a practical problem and a hot research topic in agent research. Most of current solutions for this problem are based on the assumption that there is no relationship between these tasks. However, logical interdependent relationships may exist between tasks so that transfer costs will be incurred when interdependent tasks are assigned to different agents. In order to solve this problem, a coalition formation strategy is proposed. In this strategy, it is allowed that agents disclose some personal cost information to compete for tasks in a controlled way. Experimental results show that, under the labor-based profit distribution framework, the information disclosure strategy is faster in forming coalitions and increases coalition net profit compared to the traditional information non-disclosure strategy.