Theory and algorithms for plan merging
Artificial Intelligence
Distributed problem solving and planning
Multiagent systems
Coordinating Plans of Autonomous Agents
Coordinating Plans of Autonomous Agents
Approximating Minimum Feedback Sets and Multi-Cuts in Directed Graphs
Proceedings of the 4th International IPCO Conference on Integer Programming and Combinatorial Optimization
Evolution of the GPGP/TÆMS Domain-Independent Coordination Framework
Autonomous Agents and Multi-Agent Systems
Plan-Coordination Mechanisms and the Price of Autonomy
Computational Logic in Multi-Agent Systems
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A multi-agent planning problem consists of a set of activities that need to be planned by several autonomous agents. Here, plan coordination methods play an important role, since independently generated plans by different agents can easily lead to an infeasible joint plan. We study a coordination-by-design approach which allows each agent to make its own plan completely independently of the others, while still guaranteeing the feasibility of the joint plan. The essence of this coordination approach is to determine a minimum number of additional constraints (a minimum coordination set) such that autonomously developed plans satisfying these constraints are always mergeable into an overall feasible plan. It has been shown that such coordination problems are very hard to solve. Therefore, approximation algorithms have been developed to compute a sufficient, but not necessarily minimum coordination set. In this paper, we concentrate on a special class of multi-agent planning problems. These problems arise in several practical applications such as supply chain management and hospital patient treatment. The plan coordination instances in these applications turn out to have a special structure. Using so-called agent dependency graphs, we show that for this special class of problems a better approximation algorithm to compute a sufficient coordination set can be obtained.