A Theory of Many-sorted Evolving Algebras

Electrical Engineering, Mathematics and Computer Scienc

Cooperative heuristic multi-agent planning

In this paper we will use the framework to study cooperative heuristic multi-agent planning. During the construction of their plans, the agents use a heuristic function inspired by the FF planner (l3l). At any time in the process of planning the agents may exchange available resources, or they may request an agent to produce a missing resource. The latter feature is anabled by an advertising mechanism: Any agent communicates to the other agents which resources it can, in principle, produce using a plan scheme stored in its knowledge base. The planning algorithm presented in this paper is sound but not complete: It might fail to find a plan in cases a valid plan does exist.Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc

Fusion of Plans in a Framework with Constraints

The promise of multi-agent systems is that multiple agents can solve problems more efficiently than single agents can. In this paper we propose a method to implement cooperation between agents in the planning phase, in order to achieve more cost-effective solutions than without cooperation. Two results are presented: First of all, we introduce a flexible framework to describe cooperation in a planning process. This framework allows us to specify the basic tasks that have to be performed in order to satisfy a set of goals, and to specify constraints to model deadlines, capacity constraints, speed limits, conficting situations, et cetera. Furthermore, we present a polynomial fusion algorithm to implement cooperation between multiple agents.Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc

A Plan Fusion Algorithm for Multi-Agent Systems

We introduce an algorithm for cooperative planning in multi-agent systems. The algorithm enables the agents to combine (fuse) their plans in order to increase their joint profits. A computational resources and skills framework is developed for representing the planned activities of an agent under time constraints. Using this resource-skill framework, we present an efficient (polynomial time) algorithm that fuses the plans of a group of agents in such a way that their joint profits improve. The framework and the algorithm are illustrated using a simplified example from the freight transport domain.Software Computer TechnologyElectrical Engineering, Mathematics and Computer Scienc