The multi variable multi constrained distributed constraint optimization framework

Service coordination in domains involving temporal constraints and duration uncertainty has previously been solved with a greedy algorithm that attempts to satisfy service requests one by one rather than reasoning over their combinations to deal with intractable problems. We propose preprocessing using that abstracts away duration uncertainty, so that the simplified problem can be solved faster and suggest which requests should be addressed first based on reward and satisfiability. We define a new generalization of MC-DCOP, called MV-MC-DCOP, and use this as our model. We present a Mixed Integer Linear Program, a Partially Centralized MV-MC-DCOP, and a fully decentralized MVMC-DCOP approach to this preprocessing, and analyze the strengths and weaknesses of each approach.

• Type: Conference
• Year: 2010
• Where: ATAL
• Authors: Christopher Portway, Edmund H. Durfee
• Keywords: ATAL 2010, Duration Uncertainty, Greedy Algorithm, Intelligent Agents, Temporal Constraints