Multiobjective, preference-based search in acyclic OR-graphs

Abstract

We consider the problem of determining a most preferred path from a start node to a goal node set in an acyclic OR-graph, given a multiattribute preference function, a multiobjective reward structure, and heuristic information about this reward structure. We present an algorithm which is shown to terminate with a most preferred path, given an admissible heuristic set. The algorithm illustrates how Artificial Intelligence techniques can be productively employed to solve multiobjective problems.