Solving Multi-Agent Flexible Planning Based On Soft Constraints

Multi-Agent planning is an extension of classical Artificial Intelligence planning. Usually multiple agents can act together to achieve planning goal. But classical multi-Agent methods require that the constraints are either totally satisfied or totally violated, which is too rigorous to formulate and to solve most of the real problems. In this paper, we define a multi-Agent flexible planning problem which supports soft constraints, and then we present a new technique called distributed flexible constraint satisfaction (CSP), which is the combination of flexible CSP and distributed CSP, to deal with this planning problem. For a given multi-Agent flexible planning problem, multiple agents can plan cooperatively with a satisfaction degree when solving the problem is difficult or infeasible, and then we can get a plan with a tradeoff between plan quality and length.More and more researchers are interested in this area due to its valuable theory research and application perspectives. New application area and developing direction are explored, for example, how to extend intelligent planning to handle the scope of planning problems. The classical planning restricts the development of planning. Such as, traditional planning only can support rigorous constraints, and has hard and imperative constraints, which are fully satisfied or fully violated. That is proved to be too restrictive. If one constraint is not totally true, it is supposed to be violated the constraint. The classical plan technique can't describe the real situation, so the flexible planning and multi-Agent planning appear.Multi-Agent planning is developed with multi-Agent system; it has the characteristics of artificial planning and distributed planning. Many real world applications can be classified into multi-Agent planning problem, and have the attributes of flexible planning problems. We can't solve multi-Agent flexible planning problems by dynamic flexible constraints satisfactory method or multi-Agent technique, because they are similar with both but not exactly in the same situation. We only pay attention to such problems in this paper. Soft constraints are introduced into multi-Agent planning, and transform into distributed flexible CSP to solve.Multi-Agent planning has many applications, such as Logistics and transport, business Management and games. It is very important to research on it.