Date of Original Version



Technical Report

Rights Management

All Rights Reserved

Abstract or Description

Abstract: "This paper explores the issue of planning in two-person games using approximately learned knowledge which is in the form of macros. A planning technique called Knowledge Enabled Planning, which consists of generating new plans by instantiating and composing the macros and testing them against the opponent's counter-plans, is introduced using a program called LEBL that learns and plans in two-person games. Some empirical results of testing LEBL in king and pawn endings in chess are presented along with a complexity analysis of the planning algorithm."