Coalitional Bargaining with Agent Type Uncertainty
Proceedings of the Twentieth International Joint Conference on Artificial Intelligence. Pages 1227-1231.
Abstract
Coalition formation is a problem of great interest in AI, allowing groups of autonomous, individually rational agents to form stable teams. Automating the negotiations underlying coalition formation is, naturally, of special concern. However, research to date in both AI and economics has largely ignored the potential presence of uncertainty in coalitional bargaining. We present a model of discounted coalitional bargaining where agents are uncertain about the types (or capabilities) of potential partners, and hence the value of a coalition. We cast the problem as a Bayesian game in extensive form, and describe its Perfect Bayesian Equilibria as the solutions to a polynomial program. We then present a heuristic algorithm using iterative coalition formation to approximate the optimal solution, and evaluate its performance.
@inproceedings{ijcai2007p198,
title = {Coalitional Bargaining with Agent Type Uncertainty},
author = {Chalkiadakis, Georgios and Boutilier, Craig},
booktitle = {Proceedings of the Twentieth International Joint Conference on
Artificial Intelligence, {IJCAI-07}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ramon López de Mántaras},
pages = {1227--1231},
year = {2007},
url = {https://ijcai.org/proceedings/2007/198},
}
TY - CPAPER TI - Coalitional Bargaining with Agent Type Uncertainty AU - Chalkiadakis, Georgios AU - Boutilier, Craig T2 - Proceedings of the Twentieth International Joint Conference on Artificial Intelligence, IJCAI-07 PB - International Joint Conferences on Artificial Intelligence PY - 2007 SP - 1227 EP - 1231 UR - https://ijcai.org/proceedings/2007/198 ER -Copied
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