Paper Info
Title
Bilateral bargaining with multiple opportunities: knowing your opponent's bargaining position
Abstract
Negotiations have been extensively studied theoretically throughout the years. A well-known bilateral approach is the ultimatum game, where two agents negotiate on how to split a surplus or a "dollar"-the proposer makes an offer and responder can choose to accept or reject. In this paper a natural extension of the ultimatum game is presented, in which both agents can negotiate with other opponents in case of a disagreement. This way the basics of a competitive market are modeled, where, for instance, a buyer can try several sellers before making a purchase decision. The game is investigated using an evolutionary simulation. The outcomes appear to depend largely on the information available to the agents. We find that if the agents' number of remaining bargaining opportunities is commonly known, the proposer has the advantage. If this information is held private, however, the responder can obtain a larger share of the surplus. For the first case we also provide a game-theoretic analysis and compare the outcome with evolutionary results. Furthermore, the effects of search costs, uncertainty about future opportunities, and allowing multiple issues to be negotiated simultaneously are investigated
Year
DOI
Venue
2006
10.1109/TSMCC.2005.860574
IEEE Transactions on Systems, Man, and Cybernetics, Part C
Keywords
Field
DocType
marketing,evolutionary algorithm,search cost,evolutionary computation,incomplete information,ultimatum game,competitive market,game theory
Mathematical optimization,Computer science,Decision support system,Ultimatum game,Search cost,Artificial intelligence,Purchasing,Perfect competition,Game theory,Machine learning,Complete information,Negotiation
Journal
Volume
Issue
ISSN
36
1
1094-6977
Citations 
PageRank 
References 
5
0.50
16
Authors
2
Name
Order
Citations
PageRank
Enrico H. Gerding175977.42
Johannes A. La Poutré230824.78