On stable social laws and qualitative equilibria
Artificial Intelligence
Online computation and competitive analysis
Online computation and competitive analysis
iBundle: an efficient ascending price bundle auction
Proceedings of the 1st ACM conference on Electronic commerce
An alternating offers bargaining model for computationally limited agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 1
Auctions with Severely Bounded Communication
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
UCP-Networks: A Directed Graphical Representation of Conditional Utilities
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Partial-revelation VCG mechanism for combinatorial auctions
Eighteenth national conference on Artificial intelligence
Auction design with costly preference elicitation
Annals of Mathematics and Artificial Intelligence
Eliciting bid taker non-price preferences in (combinatorial) auctions
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Incremental utility elicitation with minimax regret decision criterion
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Complexity of mechanism design
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Cooperative negotiation in autonomic systems using incremental utility elicitation
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Resource selection games with unknown number of players
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A Technique for Large Automated Mechanism Design Problems
IAT '06 Proceedings of the IEEE/WIC/ACM international conference on Intelligent Agent Technology
Learning equilibrium as a generalization of learning to optimize
Artificial Intelligence
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
As Safe As It Gets: Near-Optimal Learning in Multi-Stage Games with Imperfect Monitoring
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Characterizing solution concepts in games using knowledge-based programs
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Mechanism design with partial revelation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Iterated regret minimization: a new solution concept
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
| Hi-index | 0.00 |
Mechanism design has found considerable application to the construction of agent-interaction protocols. In the standard setting, the type (e.g., utility function) of an agent is not known by other agents, nor is it known by the mechanism designer. When this uncertainty is quantified probabilistically, a mechanism induces a game of incomplete information among the agents. However, in many settings, uncertainty over utility functions cannot easily be quantified. We consider the problem of incomplete information games in which type uncertainty is strict or unquantified. We propose the use of minimax regret as a decision criterion in such games, a robust approach for dealing with type uncertainty. We define minimax-regret equilibria and prove that these exist in mixed strategies for finite games. We also consider the problem of mechanism design in this framework by adopting minimax regret as an optimization criterion for the designer itself, and study automated optimization of such mechanisms.