Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Why AM an EUISKO appear to work.
Artificial Intelligence
Recursive estimation and time-series analysis: an introduction
Recursive estimation and time-series analysis: an introduction
Knowledge-based feature generation
Proceedings of the sixth international workshop on Machine learning
Incremental Learning from Noisy Data
Machine Learning
A result on the computational complexity of heuristic estimates for the A* algorithm
IJCAI'83 Proceedings of the Eighth international joint conference on Artificial intelligence - Volume 2
Constructive induction on decision trees
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Discovering admissible heuristics by abstracting and optimizing: a transformational approach
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
A problem similarity approach to devising heuristics: first results
IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1
Failsafe: a floor planner that uses EBG to learn from its failures
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
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It is well-known that inductive learning algorithms are sensitive to the way in which examples of a concept are represented. Constructive induction reduces this sensitivity by enabling the inductive algorithm to create new terms with which to describe examples. However, new terms are usually created as functions of existing terms, so an extremely poor initial representation makes the search for new terms intractable. This work considers inductive learning within a problem-solving environment. It shows that information about the problem-solving task can be used to create terms that are suitable for learning search control knowledge. The resulting terms describe the problem-solver's progress in achieving its goals. Experimental evidence from two domains is presented in support of the approach.