Directed soft arc consistency in pseudo trees

We propose an efficient method that applies directed soft arc consistency to a Distributed Constraint Optimization Problem (DCOP) which is a fundamental framework of multi-agent systems. With DCOPs a multi-agent system is represented as a set of variables and a set of constraints/cost functions. We focus on DCOP solvers that employ pseudo-trees. A pseudo-tree is a graph structure for a constraint network that represents a partial ordering of variables. Most pseudo-tree-based search algorithms perform optimistic searches using explicit/implicit backtracking in parallel. However, for cost functions taking a wide range of cost values, such exact algorithms require many search iterations, even if the constraint density is relatively low. Therefore additional improvements are necessary to reduce the search process. A previous study used a dynamic programming-based preprocessing technique that estimates the lower bound values of costs. However, there are opportunities for further improveme...

• Type: Conference
• Year: 2009
• Where: ATAL
• Authors: Toshihiro Matsui, Marius-Calin Silaghi, Katsutoshi Hirayama, Makoto Yokoo, Hiroshi Matsuo
• Keywords: Artificial Intelligence, ATAL 2009, Lower Bound, Lower Bound Value, Soft Arc Consistency