TY - GEN
T1 - The significance of bidding, accepting and opponent modeling in automated negotiation
AU - Baarslag, Tim
AU - Dirkzwager, Alexander
AU - Hindriks, Koen V.
AU - Jonker, Catholijn M.
PY - 2014
Y1 - 2014
N2 - Given the growing interest in automated negotiation, the search for effective strategies has produced a variety of different negotiation agents. Despite their diversity, there is a common structure to their design. A negotiation agent comprises three key components: the bidding strategy, the opponent model and the acceptance criteria. We show that this three-component view of a negotiating architecture not only provides a useful basis for developing such agents but also provides a useful analytical tool. By combining these components in varying ways, we are able to demonstrate the contribution of each component to the overall negotiation result, and thus determine the key contributing components. Moreover, we study the interaction between components and present detailed interaction effects. Furthermore, we find that the bidding strategy in particular is of critical importance to the negotiator's success and far exceeds the importance of opponent preference modeling techniques. Our results contribute to the shaping of a research agenda for negotiating agent design by providing guidelines on how agent developers can spend their time most effectively.
AB - Given the growing interest in automated negotiation, the search for effective strategies has produced a variety of different negotiation agents. Despite their diversity, there is a common structure to their design. A negotiation agent comprises three key components: the bidding strategy, the opponent model and the acceptance criteria. We show that this three-component view of a negotiating architecture not only provides a useful basis for developing such agents but also provides a useful analytical tool. By combining these components in varying ways, we are able to demonstrate the contribution of each component to the overall negotiation result, and thus determine the key contributing components. Moreover, we study the interaction between components and present detailed interaction effects. Furthermore, we find that the bidding strategy in particular is of critical importance to the negotiator's success and far exceeds the importance of opponent preference modeling techniques. Our results contribute to the shaping of a research agenda for negotiating agent design by providing guidelines on how agent developers can spend their time most effectively.
UR - https://www.scopus.com/pages/publications/84923120416
UR - https://www.scopus.com/inward/citedby.url?scp=84923120416&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-419-0-27
DO - 10.3233/978-1-61499-419-0-27
M3 - Conference contribution
AN - SCOPUS:84923120416
T3 - Frontiers in Artificial Intelligence and Applications
SP - 27
EP - 32
BT - ECAI 2014 - 21st European Conference on Artificial Intelligence, Including Prestigious Applications of Intelligent Systems, PAIS 2014, Proceedings
A2 - Schaub, Torsten
A2 - Friedrich, Gerhard
A2 - O'Sullivan, Barry
PB - IOS Press
T2 - 21st European Conference on Artificial Intelligence, ECAI 2014
Y2 - 18 August 2014 through 22 August 2014
ER -