A* Heuristic Based on a Hierarchical Space Model Extracted from Game Replays

The paper presents a new method of building a hierarchical model of the state space.The model is extracted fully automatically from game replays that store executed plan traces.It is used by a novel approach for estimating the distance between states in a state-space graph.The estimate is applied in the A* algorithm as a heuristic function to reduce the search space.The method was validated using the game Smart Blocks.It is a testbed environment for studying methods that benefit from game replay analysis.The proposed heuristic is dedicated to difficult classical planning problems, for which problem-specific or automated heuristics are difficult to obtain.

Abstract licence: CC BY

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