Learning General Search Control from Outside Guidance
Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Knowledge Acquisition. Pages 334-336.
Abstract
The system presented here shows how Soar, an architecture for general problem solving and learning, can acquire general search-control knowledge from outside guidance. The guidance can be either direct advice about what the system should do, or a problem that illustrates a relevant idea. The system makes use of the guidance by first formulating an appropriate goal for itself. In the process of achieving this goal, it learns general search-control chunks. In the case of learning from direct advice, the goal is to verify that the advice is correct. The verification allows the system to obtain general conditions of applicability of the advice, and to protect itself from erroneous advice. The system learns from illustrative problems by setting the goal of solving the problem provided. It can then transfer the lessons it learns along the way to its original problem . This transfer constitutes a rudimentary form of analogy.
@inproceedings{ijcai1987p69,
title = {Learning General Search Control from Outside Guidance},
author = {Golding, Andrew R. and Rosenbloom, Paul S. and Laird, John E.},
booktitle = {Proceedings of the Tenth International Joint Conference on
Artificial Intelligence, {IJCAI-87}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John McDermott},
pages = {334--336},
year = {1987},
note = {Knowledge Acquisition},
url = {https://ijcai.org/proceedings/1987/69},
}
TY - CPAPER TI - Learning General Search Control from Outside Guidance AU - Golding, Andrew R. AU - Rosenbloom, Paul S. AU - Laird, John E. T2 - Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87 PB - International Joint Conferences on Artificial Intelligence PY - 1987 SP - 334 EP - 336 UR - https://ijcai.org/proceedings/1987/69 ER -Copied
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