Multiagent systems: a modern approach to distributed artificial intelligence
Multiagent systems: a modern approach to distributed artificial intelligence
Algorithms, games, and the internet
STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Prisoner's Dilemma
Automated negotiation and decision making in multiagent environments
Mutli-agents systems and applications
Protocols for Negotiating Complex Contracts
IEEE Intelligent Systems
Effective bidding and deal identification for negotiations in highly nonlinear scenarios
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Multi-issue negotiation protocol for agents: exploring nonlinear utility spaces
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Eliminating interdependencies between issues for multi-issue negotiation
CIA'06 Proceedings of the 10th international conference on Cooperative Information Agents
Max-Product for Maximum Weight Matching: Convergence, Correctness, and LP Duality
IEEE Transactions on Information Theory
Equilibrium approximation in simulation-based extensive-form games
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Autonomous Agents and Multi-Agent Systems
| Hi-index | 0.00 |
There is a number of recent research lines addressing complex negotiations in highly rugged utility spaces. However, most of them focus on overcoming the problems imposed by the complexity of the scenario, without analyzing the strategic behavior of the agents in the models they propose. Analyzing the dynamics of the negotiation process when agents with different strategies interact is necessary to apply these models to real, competitive environments, where agents cannot be supposed to behave in the same way. Specially problematic are situations like the well-known prisoner's dilemma, or more generally, situations of high price of anarchy. These situations imply that individual rationality drives the agents towards strategies which yield low individual and social welfares. In highly rugged scenarios, such situations usually make agents fail to reach an agreement, and therefore negotiation mechanisms should be designed to avoid them. This paper performs a strategy analysis of an auction-based negotiation model designed for highly rugged scenarios, revealing that the approach is prone to the prisoner's dilemma. In addition, a set of techniques to solve this problem are proposed, and an experimental evaluation is performed to validate the adequacy of the proposed approaches to improve the strategic stability of the negotiation process.