Alternating-offers bargaining with one-sided uncertain deadlines: an efficient algorithm
Artificial Intelligence
An analysis of feasible solutions for multi-issue negotiation involving nonlinear utility functions
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Game Theoretical Insights in Strategic Patrolling: Model and Algorithm in Normal-Form
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Annals of Mathematics and Artificial Intelligence
An algorithmic game theory framework for bilateral bargaining with uncertainty
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Equilibrium approximation in simulation-based extensive-form games
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Studying the impact of negotiation environments on negotiation teams' performance
Information Sciences: an International Journal
Bilateral bargaining with one-sided uncertain reserve prices
Autonomous Agents and Multi-Agent Systems
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In this paper we study multi issue alternating-offers bargaining in a perfect information finite horizon setting, we determine the pertinent subgame perfect equilibrium, and we provide an algorithm to compute it. The equilibrium is determined by making a novel use of backward induction together with convex programming techniques in multi issue settings. We show that the agents reach an agreement immediately and that such an agreement is Pareto efficient. Furthermore, we prove that, when the multi issue utility functions are linear, the problem of computing the equilibrium is tractable and the related complexity is polynomial with the number of issues and linear with the deadline of bargaining.