The Avoidance of (Relative) Catastrophe, Heuristic Competence, Genuine Dynamic Weighting and Computational Issues in Heuristic Problem Solving
Proceedings of the Third International Joint Conference on Artificial Intelligence. Theory of Heuristic Search. Pages 12-16.
Abstract
To solve difficult problems heuristically, requires detailed attention to computational efficiency. This paper describes how a heuristic problem solving system, HPA, attempts to find a near optimal solution to the traveling salesman problem. A critical innovation over previous search algorithms is an explicit dynamic weighting of the heuristic information. The heuristic information is weighted inversely proportional to its depth in the search tree--in consequence it produces a narrower depth first search than traditional weightings. At the same time, dynamic weighting retains the catastrophe protection of ordinary branch and bound algorithms.
@inproceedings{ijcai1973p2,
title = {The Avoidance of (Relative) Catastrophe, Heuristic Competence, Genuine Dynamic Weighting and Computational Issues in Heuristic Problem Solving},
author = {Pohl, Ira},
booktitle = {Proceedings of the Third International Joint Conference on
Artificial Intelligence, {IJCAI-73}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Nils J. Nilsson},
pages = {12--16},
year = {1973},
month = {8},
note = {Theory of Heuristic Search},
url = {https://ijcai.org/proceedings/1973/2},
}
TY - CPAPER TI - The Avoidance of (Relative) Catastrophe, Heuristic Competence, Genuine Dynamic Weighting and Computational Issues in Heuristic Problem Solving AU - Pohl, Ira T2 - Proceedings of the Third International Joint Conference on Artificial Intelligence, IJCAI-73 PB - International Joint Conferences on Artificial Intelligence PY - 1973 SP - 12 EP - 16 UR - https://ijcai.org/proceedings/1973/2 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
