Name
Abstract | ||
|---|---|---|
Multi-issue negotiation protocols have been studied widely and represent a promising field since most negotiation problems in the real world involve interdependent multiple issues. The vast majority of this work has assumed that negotiation issues are independent, so agents can aggregate the utilities of the issue values by simple summation, producing linear utility functions. In the real world, however, such aggregations are often unrealistic. We cannot, for example, just add up the value of car's carburetor and the value of car's engine when engineers negotiate over the design a car. These value of these choices are interdependent, resulting in nonlinear utility functions. In this paper, we address this important gap in current negotiation techniques. We propose a negotiation protocol where agents employ adjusted sampling to generate proposals, and a bidding-based mechanism is used to find social-welfare maximizing deals. Our experimental results show that our method substantially outperforms existing methods in large non-linear utility spaces like those found in real world contexts. |
Year | Venue | Keywords |
|---|---|---|
2007 | IJCAI | negotiation issue,large non-linear utility space,current negotiation technique,real world,nonlinear utility space,linear utility function,nonlinear utility function,issue value,negotiation problem,negotiation protocol,multi-issue negotiation protocol,social welfare |
Field | DocType | Citations |
Interdependence,Nonlinear system,Industrial engineering,Computer science,Sampling (statistics),Artificial intelligence,Bidding,Machine learning,Negotiation | Conference | 72 |
PageRank | References | Authors |
3.45 | 9 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Takayuki Ito | 1 | 888 | 380.66 |
| Hiromitsu Hattori | 2 | 222 | 25.09 |
| Mark M. Klein | 3 | 1550 | 187.52 |