A Computational Model of Analogical Problem Solving
Proceedings of the Seventh International Joint Conference on Artificial Intelligence. Learning. Pages 147-151.
Abstract
This paper outlines a theory of analogical reasoning based on a process-model of problem solving by analogy and the hypothesis that problem solving and learning are inalienable, concurrent processes in the human cognitive system . The analogical problem solver exploits prior experience in solving similar problems, and, in the process, augments a hierarchically-structured epsiodic long term memory . An analogical transformation process is developed based on a modified version of Means-Ends Analysis in order to map past solutions from similar problems into solutions satisfying the requirements of the new problem.
@inproceedings{ijcai1981p31,
title = {A Computational Model of Analogical Problem Solving},
author = {Carbonell, Jaime G.},
booktitle = {Proceedings of the Seventh International Joint Conference on
Artificial Intelligence, {IJCAI-81}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Roger C. Schank},
pages = {147--151},
year = {1981},
month = {8},
note = {Learning},
url = {https://ijcai.org/proceedings/1981/31},
}
TY - CPAPER TI - A Computational Model of Analogical Problem Solving AU - Carbonell, Jaime G. T2 - Proceedings of the Seventh International Joint Conference on Artificial Intelligence, IJCAI-81 PB - International Joint Conferences on Artificial Intelligence PY - 1981 SP - 147 EP - 151 UR - https://ijcai.org/proceedings/1981/31 ER -Copied
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