The interaction of people with autonomous agents has become increasingly prevalent. Some of these settings include security domains, where people can be characterized as uncooperative, hostile, manipulative, and tending to take advantage of the situation for their own needs. This makes it challenging to design proficient agents to interact with people in such environments. Evaluating the success of the agents automatically before evaluating them with people or deploying them could alleviate this challenge and result in better designed agents. In this paper we show how Peer Designed Agents (PDAs) - computer agents developed by human subjects - can be used as a method for evaluating autonomous agents in security domains. Such evaluation can reduce the effort and costs involved in evaluating autonomous agents interacting with people to validate their efficacy. Our experiments included more than 70 human subjects and 40 PDAs developed by students. The study provides empirical support that PDAs can be used to compare the proficiency of autonomous agents when matched with people in security domains.

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In Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence, August 2011.

@inproceedings{AAAI11-Lin, title={Comparing Agents: Success against People in Security Domains}, author={Raz Lin and Sarit Kraus and Noa Agmon and Samuel Barrett and Peter Stone}, booktitle={Proceedings of the Twenty-Fifth AAAI Conference on Artificial Intelligence}, month={August}, url="http://nn.cs.utexas.edu/?AAAI11-Lin", year={2011} }