Hierarchical Credit Allocation in a Classifier System
Proceedings of the Tenth International Joint Conference on Artificial Intelligence. Knowledge Acquisition. Pages 217-219.
Abstract
Learning systems which engage in sequential activity face the problem of properly allocating credit to steps or actions which make possible later steps that result in environmental payoff. In the classifier systems studied by Holland and others, credit is allocated by means of a "bucketbrigade" algorithm through which, over time, environmental payoff in effect Bows back to classifiers which take early, stage-setting actions. The algorithm has advantages of simplicity and locality, but may not adequately reinforce long action sequences. We suggest an alternative form for the algorithm and the system 's operating principles designed to induce behavioral hierarchies in which modularity of the hierarchy would keep all bucket- brigade chains short, thus more reinforceable and more rapidly learned, but overall action sequences could be long.
@inproceedings{ijcai1987p44,
title = {Hierarchical Credit Allocation in a Classifier System},
author = {Wilson, Stewart W.},
booktitle = {Proceedings of the Tenth International Joint Conference on
Artificial Intelligence, {IJCAI-87}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {John McDermott},
pages = {217--219},
year = {1987},
note = {Knowledge Acquisition},
url = {https://ijcai.org/proceedings/1987/44},
}
TY - CPAPER TI - Hierarchical Credit Allocation in a Classifier System AU - Wilson, Stewart W. T2 - Proceedings of the Tenth International Joint Conference on Artificial Intelligence, IJCAI-87 PB - International Joint Conferences on Artificial Intelligence PY - 1987 SP - 217 EP - 219 UR - https://ijcai.org/proceedings/1987/44 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
