Strategies for Learning Search Control Rules: An Explanation-based Approach
Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Knowledge Acquisition. Pages 228-234.
Abstract
Previous work In explanation-based learning has primarily focused on developing problem solvers that learn by observing solutions. However, learning from solutions Is only one strategy for Improving performance. This paper describes how the PRODIGY system uaes explanation-based specializAtion to learn from a variety of phenomena, Including solutions, failures, and goal-interactions. Explicit tllrget concepts describe these phenomena, and each target concept Is associated with a strategy for dynamically Improving the performance of the problem solver. Explanations are formulated using a theory describing the domain and the PRODIGY problem solver. Both the target concepts and the theory are declaratively specified and extensible.
@inproceedings{ijcai1987p46,
title = {Strategies for Learning Search Control Rules: An Explanation-based Approach},
author = {Minton, Steven and Carbonell, Jaime G.},
booktitle = {Proceedings of the Tenth International Joint Conference on
Artificial Intelligence, {IJCAI-87}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John McDermott},
pages = {228--234},
year = {1987},
note = {Knowledge Acquisition},
url = {https://ijcai.org/proceedings/1987/46},
}
TY - CPAPER TI - Strategies for Learning Search Control Rules: An Explanation-based Approach AU - Minton, Steven AU - Carbonell, Jaime G. T2 - Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87 PB - International Joint Conferences on Artificial Intelligence PY - 1987 SP - 228 EP - 234 UR - https://ijcai.org/proceedings/1987/46 ER -Copied
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