Applying adversarial planning techniques to Go

Approaches to computer game playing based on alpha-beta search of the tree of possible move sequences combined with a position evaluation function hav e been successful for many games, notably Chess. Such approaches are less s uccessful for games with large search spaces and complex positions, such as Go, and we are led to seek alternatives. One such alternative is to model the goals of the players, and their strategies for achieving these goals. T his approach means searching the space of possible goal expansions, typical ly much smaller than the space of move sequences. Previous attempts to appl y these techniques to Go have been unable to provide results for anything o ther than a high strategic level or very open game positions. In this paper we describe how adversarial hierarchical task network planning can provide a framework for goal-directed game playing in Go which is also applicable both strategic and tactical problems. (C) 2001 Elsevier Science B.V. All ri ghts reserved.