Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
On the approximation of maximum satisfiability
SODA selected papers from the third annual ACM-SIAM symposium on Discrete algorithms
Algorithmic mechanism design (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Distributed rational decision making
Multiagent systems
Computationally feasible VCG mechanisms
Proceedings of the 2nd ACM conference on Electronic commerce
Approximation algorithms
Strategic negotiation in multiagent environments
Strategic negotiation in multiagent environments
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Introduction to Algorithms
Truth revelation in approximately efficient combinatorial auctions
Journal of the ACM (JACM)
The complexity of theorem-proving procedures
STOC '71 Proceedings of the third annual ACM symposium on Theory of computing
Approximation Algorithms for MAX SAT: Yannakakis vs. Goemans-Williamson
ISTCS '97 Proceedings of the Fifth Israel Symposium on the Theory of Computing Systems (ISTCS '97)
Mechanism Design for Resource Bounded Agents
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
Bounded rationality in repeated games and mechanism design for agents in computational settings
Bounded rationality in repeated games and mechanism design for agents in computational settings
| Hi-index | 0.00 |
We investigate the mechanism design problem when the agents and the mechanism have computational restrictions. In particular, we examine how results in the mechanism design literature are affected when the social choice rule requires the mechanism to solve a computationally difficult optimization problem. Both dominant strategy and Nash implementation are considered for a multiagent version of the maximum satisfiability problem. We show that the best a mechanism can guarantee is that at least half of the maximum number of simultaneously satisfiable agents will be satisfied by the outcome. Our analysis highlights some of the difficulties that arise in applying results from mechanism design to computational problems. In particular, our results show that using approximation in multiagent settings can be much less successful than in traditional computational settings because of the game theoretic guarantees required of the outcomes.