Some studies in machine learning using the game of checkers
Computers & thought
Experiments in automatic learning for a multipurpose hueristic program
Communications of the ACM
Thinking Computer: Mind inside Matter
Thinking Computer: Mind inside Matter
Performance measurement and analysis of certain search algorithms.
Performance measurement and analysis of certain search algorithms.
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
Automated Creation of Pattern Database Search Heuristics
Model Checking and Artificial Intelligence
Constructive induction on domain information
AAAI'91 Proceedings of the ninth National conference on Artificial intelligence - Volume 2
Generating effective admissible heuristics by abstraction and reconstitution
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Hierarchical A *: searching abstraction hierarchies efficiently
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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Here we describe an approach, based upon a notion of problem similarity, that can be used when attempting to devise a heuristic for a given search problem (of a sort represented by graphs). The proposed approach relies on a change in perspective: instead of seeking a heuristic directly for a given problem P1, one seeks Instead a problem P2 easier to solve than P1 and related to P1 in a certain way. The next step is to find an algorithm for finding paths in P2, then apply this algorithm in a certain way as a heuristic for P1. In general, the approach is to consider as candidates problems P2 that are "edge subgraphs" or "edge supergraphs" of the given problem P1. As a non-trivial application, we show that a certain restricted form of sorting problem (serving as P2) is an edge supergraph of the 8-puzzle graph (P1). A simple algorithm for solving this sorting problem is evident, and the number of swaps executed in solving an instance thereof is taken as a heuristic estimate of distance between corresponding points in the 8-puzzle graph. Using the At algorithm, we experimentally compare the performance of this "maxsort" heuristic for the 8-puzzle with others in the literature. Hence we present evidence of a role for exploiting certain similarities among problems to transfer a heuristic from one problem to another, from an "easier" problem to a "harder" one.