Research Article
Learning Models of the Negotiation Partner in Spatio-temporal Collaboration
@INPROCEEDINGS{10.1007/978-3-642-03354-4_18, author={Yi Luo and Ladislau B\o{}l\o{}ni}, title={Learning Models of the Negotiation Partner in Spatio-temporal Collaboration}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 4th International Conference, CollaborateCom 2008, Orlando, FL, USA, November 13-16, 2008, Revised Selected Papers}, proceedings_a={COLLABORATECOM}, year={2012}, month={5}, keywords={}, doi={10.1007/978-3-642-03354-4_18} }- Yi Luo
Ladislau Bölöni
Year: 2012
Learning Models of the Negotiation Partner in Spatio-temporal Collaboration
COLLABORATECOM
Springer
DOI: 10.1007/978-3-642-03354-4_18
Abstract
We describe an approach for learning the model of the opponent in spatio-temporal negotiation. We use the Children in the Rectangular Forest canonical problem as an example. The opponent model is represented by the physical characteristics of the agents: the current location and the destination. We assume that the agents do not disclose any of their information voluntarily; the learning needs to rely on the study of the offers exchanged during normal negotiation. Our approach is Bayesian learning, with the main contribution being four techniques through which the posterior probabilities are determined. The calculations rely on (a) feasibility of offers, (b) rationality of offers, (c) the assumption of decreasing utility, and (d) the assumption of accepting offer which is better than the next counter-offer.
