Behavior Bounding: Toward Effective Comparisons of Agents & Humans
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 727-731.
Abstract
In this paper, we examine methods for comparing human and agent behavior. The results of such a comparison can be used to validate a computer model of human behavior, score a Turning test, or guide an intelligent tutoring system. We introduce behavior bounding, an automated model-based approach for behavior comparison. We identity how this approach can be used with both human and agent behavior. We demonstrate that it requires minimal human effort to use, and that it is efficient when working with complex agents. Finally, we show empirical results indicating that this approach is effective at identifYing behavioral problems in certain types of agents and that it has superior performance when compared against two benchmarks.
@inproceedings{ijcai2003p106,
title = {Behavior Bounding: Toward Effective Comparisons of Agents & Humans},
author = {Wallace, Scott A. and Laird, John E.},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {727--731},
year = {2003},
url = {https://ijcai.org/proceedings/2003/106},
}
TY - CPAPER TI - Behavior Bounding: Toward Effective Comparisons of Agents & Humans AU - Wallace, Scott A. AU - Laird, John E. T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 727 EP - 731 UR - https://ijcai.org/proceedings/2003/106 ER -Copied
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