Abstract
Computer agents are increasingly deployed in settings in which they make decisions with people, such as electronic commerce, collaborative interfaces, and cognitive assistants. However, the scientific evaluation of computational strategies for human-computer decision-making is a costly process, involving time, effort and personnel. This paper investigates the use of Peer Designed Agents (PDA)-computer agents developed by human subjects-as a tool for facilitating the evaluation process of automatic negotiators that were developed by researchers. It compares the performance between automatic negotiators that interacted with PDAs to automatic negotiators that interacted with actual people in different domains. The experiments included more than 300 human subjects and 50 PDAs developed by students. Results showed that the automatic negotiators outperformed PDAs in the same situations in which they outperformed people, and that on average, they exhibited the same measure of generosity towards their negotiation partners. These patterns occurred for all types of domains, and for all types of automated negotiators, despite the fact that there were individual differences between the behavior of PDAs and people. The study thus provides an empirical proof that PDAs can alleviate the evaluation process of automatic negotiators, and facilitate their design.
Original language | English |
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Title of host publication | Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010 |
Publisher | AAAI press |
Pages | 817-822 |
Number of pages | 6 |
ISBN (Electronic) | 9781577354642 |
State | Published - 15 Jul 2010 |
Event | 24th AAAI Conference on Artificial Intelligence, AAAI 2010 - Atlanta, United States Duration: 11 Jul 2010 → 15 Jul 2010 |
Publication series
Name | Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2010 |
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Conference
Conference | 24th AAAI Conference on Artificial Intelligence, AAAI 2010 |
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Country/Territory | United States |
City | Atlanta |
Period | 11/07/10 → 15/07/10 |
Bibliographical note
Publisher Copyright:© 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Funding
∗This research is based upon work supported in part by the U.S. Army Research Laboratory and the U.S. Army Research Office under grant number W911NF-08-1-0144 and under NSF grant 0705587. Copyright ©c 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
Funders | Funder number |
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National Science Foundation | 0705587 |
Army Research Office | W911NF-08-1-0144 |
Army Research Laboratory |