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Automated Agents that Proficiently Negotiate with People: Can We Keep People out of the Evaluation Loop

  • Raz Lin
  • Yinon Oshrat
  • Sarit Kraus
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 383)

Abstract

Research on automated negotiators has flourished in recent years. Among the important issues considered is how these automated negotiators can proficiently negotiate with people. To validate this, many experimentations with people are required. Nonetheless, conducting experiments with people is timely and costly, making the evaluation of these automated negotiators a very difficult process. Moreover, each revision of the agent’s strategies requires to gather an additional set of people for the experiments. In this paper we investigate the use of Peer Designed Agents (PDAs) – computer agents developed by human subjects – as a method for evaluating automated negotiators. We have examined the negotiation results and its dynamics in extensive simulations with more than 300 human negotiators and more than 50 PDAs in two distinct negotiation environments. Results show that computer agents perform better than PDAs in the same negotiation contexts in which they perform better than people, and that on average, they exhibit the same measure of generosity towards their negotiation partners. Thus, we found that using the method of peer designed negotiators embodies the promise of relieving some of the need for people when evaluating automated negotiators.

Keywords

Multiagent System Strategy Method Bilateral Negotiation Automate Negotiation Cooperation Level 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Computer ScienceBar-Ilan UniversityRamat-GanIsrael
  2. 2.Institute for Advanced Computer StudiesUniversity of MarylandCollege ParkUSA

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