Flexible Learning of Problem Solving Heuristics Through Adaptive Search
Proceedings of the Eighth International Joint Conference on Artificial Intelligence. Learning and Knowledge Acquisition. Pages 422-424.
Abstract
Noting th at th e methods employed by ex istin g learnin g sys tems are often bound to th r: intended task domain and have little applicabi lity outside that do main, tli is paper co nsiders an :.\lterna ti ve learning sys tem design th at offers g reater fl ex ibility with o ut sacrifi c ing performance. An operational prototype, co nstru cted around a powerful adap tive searc h technique, is presented and appli ed to th e problem of acquiring problem so lving heuristics through experi ence. S om e performance results obt ai ned with th e system in a poker betting do main are reported and compared with th ose of a pr ev iously in vesti ga ted learning sys tem in th e same domain . It is seen th at comp arable levels of performance are achieved by th e two system s. despite the latter 's dependence on a considerable a mount of domain specific knowl edge for effective operation.
@inproceedings{ijcai1983p102,
title = {Flexible Learning of Problem Solving Heuristics Through Adaptive Search},
author = {Smith, Stephen F.},
booktitle = {Proceedings of the Eighth International Joint Conference on
Artificial Intelligence, {IJCAI-83}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Alan Bundy},
pages = {422--424},
year = {1983},
note = {Learning and Knowledge Acquisition},
url = {https://ijcai.org/proceedings/1983/102},
}
TY - CPAPER TI - Flexible Learning of Problem Solving Heuristics Through Adaptive Search AU - Smith, Stephen F. T2 - Proceedings of the Eighth International Joint Conference on Artificial Intelligence, IJCAI-83 PB - International Joint Conferences on Artificial Intelligence PY - 1983 SP - 422 EP - 424 UR - https://ijcai.org/proceedings/1983/102 ER -Copied
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