Automated mechanism design: A new application area for search algorithms

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2833, Issue , 2003, Pages 19-36

  Sandholm, Tuomas ^a  

^a Carnegie Mellon University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER PROGRAMMING; CONSTRAINT THEORY; MACHINE DESIGN;

AUTOMATED MECHANISM DESIGNS; IMPOSSIBILITY RESULTS; MECHANISM DESIGN; NEW APPLICATIONS; PROBLEM REPRESENTATION; SEARCH ALGORITHMS; SPECIFIC PROBLEMS; VOTING PROTOCOLS;

DESIGN;

EID: 35248882388     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-45193-8_2     Document Type: Article

References (56)

1. Mark Armstrong. Optimal multi-object auctions. Review of Economic Studies, 67:455-481, 2000.
2. Kenneth Arrow. The property rights doctrine and demand revelation under incomplete information. In M Boskin, editor, Economics and human welfare. New York Academic Press, 1979.
3. R Aumann. Acceptable points in general cooperative n-person games, volume IV of Contributions to the Theory of Games. Princeton University Press, 1959.
4. Christopher Avery and Terrence Hendershott. Bundling and optimal auctions of multiple products. Review of Economic Studies, 67:483-497, 2000.
5. John J. Bartholdi, III and James B. Orlin. Single transferable vote resists strategic voting. Social Choice and Welfare, 8(4):341-354, 1991.
6. John J. Bartholdi, III, Craig A. Tovey, and Michael A. Trick. The computational difficulty of manipulating an election. Social Choice and Welfare, 6(3):227-241, 1989.
7. B Douglas Bernheim, Bezalel Peleg, and Michael D Whinston. Coalition-proof Nash equilibria: I concepts. Journal of Economic Theory, 42(1):1-12, June 1987.
8. Avrim Blum, Jeffrey Jackson, Tuomas Sandholm, and Martin Zinkevich. Preference elicitation and query learning. In Conference on Learning Theory (COLT), Washington, D.C., 2003.
9. E H Clarke. Multipart pricing of public goods. Public Choice, 11:17-33, 1971.
10. Wolfram Conen and Tuomas Sandholm. Preference elicitation in combinatorial auctions: Extended abstract. In Proceedings of the ACM Conference on Electronic Commerce (ACM-EC), pages 256-259, Tampa, FL, October 2001.
11. A more detailed description of the algorithmic aspects appeared in the IJCAI-2001 Workshop on Economic Agents, Models, and Mechanisms, pp. 71-80.
12. Wolfram Conen and Tuomas Sandholm. Differential-revelation VCG mechanisms for combinatorial auctions. In AAMAS-02 workshop on Agent-Mediated Electronic Commerce (AMEC), Bologna, Italy, 2002.
13. Wolfram Conen and Tuomas Sandholm. Partial-revelation VCG mechanism for combinatorial auctions. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 367-372, Edmonton, Canada, 2002.
14. Vincent Conitzer, Jerome Lang, and Tuomas Sandholm. How many candidates are needed to make elections hard to manipulate? In Theoretical Aspects of Rationality and Knowledge (TARK IX), Bloomington, Indiana, USA, 2003.
15. Vincent Conitzer and Tuomas Sandholm. Automated mechanism design: Complexity results stemming from the single-agent setting, 2002. Draft.
16. Vincent Conitzer and Tuomas Sandholm. Complexity of manipulating elections with few candidates. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 314-319, Edmonton, Canada, 2002.
17. Vincent Conitzer and Tuomas Sandholm. Complexity of mechanism design. In Proceedings of the 18th Annual Conference on Uncertainty in Artificial Intelligence (UAI-02), pages 103-110, Edmonton, Canada, 2002.
18. Vincent Conitzer and Tuomas Sandholm. Vote elicitation: Complexity and strategy-proofness. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 392-397, Edmonton, Canada, 2002.
19. Vincent Conitzer and Tuomas Sandholm. An algorithm for single-agent deterministic automated mechanism design without payments. In IJCAI-03 workshop on Distributed Constraint Reasoning (DCR), Acapulco, Mexico, 2003.
20. Vincent Conitzer and Tuomas Sandholm. Applications of automated mechanism design. In UAI-03 workshop on Bayesian Modeling Applications, Acapulco, Mexico, 2003.
21. Vincent Conitzer and Tuomas Sandholm. Automated mechanism design for a self-interested designer. In Proceedings of the ACM Conference on Electronic Commerce (ACM-EC), pages 232-233, San Diego, CA, 2003. Poster paper. Full-length draft available at www.cs.cmu.edu/~sandholm/.
22. Vincent Conitzer and Tuomas Sandholm. Automated mechanism design with a structured outcome space, 2003.
23. Vincent Conitzer and Tuomas Sandholm. Computational criticisms of the revelation principle. In AAMAS-03 workshop on Agent-Mediated Electronic Commerce (AMEC), Melbourne, Australia, 2003. Poster paper.
24. Vincent Conitzer and Tuomas Sandholm. Universal voting protocol tweaks to make manipulation hard. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI), Acapulco, Mexico, 2003.
25. C d'Aspremont and L A Gérard-Varet. Incentives and incomplete information. Journal of Public Economics, 11:25-45, 1979.
26. A Gibbard. Manipulation of voting schemes. Econometrica, 41:587-602, 1973.
27. J Green and J-J Laffont. Incentives in Public Decision Making. Amsterdam: North-Holland, 1979.
28. Theodore Groves. Incentives in teams. Econometrica, 41:617-631, 1973.
29. Eric Hsu. Automated mechanism design: Type space and exponential auction. In AAMAS-03 workshop on Evolutionary Game Theory for Learning in MAS, Melbourne, Australia, 2003.
30. Benoit Hudson and Tuomas Sandholm. Effectiveness of preference elicitation in combinatorial auctions. In AAMAS-02 workshop on Agent-Mediated Electronic Commerce (AMEC), Bologna, Italy, 2002. Extended version: Carnegie Mellon University, Computer Science Department, CMU-CS-02-124, March.
31. Also: Stanford Institute for Theoretical Economics workshop (SITE-02).
32. Anthony Jameson, Christopher Hackl, and Thomas Kleinbauer. Evaluation of automatically designed mechanisms. In UAI-03 workshop on Bayesian Modeling Applications, Acapulco, Mexico, 2003.
33. Kate Larson and Tuomas Sandholm. Bargaining with limited computation: Deliberation equilibrium. Artificial Intelligence, 132(2):183-217, 2001.
34. Short early version appeared in the Proceedings of the National Conference on Artificial Intelligence (AAAI), pp. 48-55, Austin, TX, 2000.
35. Kate Larson and Tuomas Sandholm. Computationally limited agents in auctions. In AGENTS-01 Workshop of Agents for B2B, pages 27-34, Montreal, Canada, May 2001.
36. Kate Larson and Tuomas Sandholm. Costly valuation computation in auctions. In Theoretical Aspects of Rationality and Knowledge (TARK VIII), pages 169-182, Sienna, Italy, July 2001.
37. Kate Larson and Tuomas Sandholm. An alternating offers bargaining model for computationally limited agents. In International Conference on Autonomous Agents and Multi-Agent Systems, Bologna, Italy, July 2002.
38. Ron Lavi, Ahuva Mu'Alem, and Noam Nisan. Towards a Characterization of Truthful Combinatorial Auctions, 2003. Draft, April 8th.
39. Anton Likhodedov and Tuomas Sandholm. Auction mechanism for optimally trading off eficiency and revenue. In AAMAS workshop on Agent-Mediated Electronic Commerce (AMEC V), Melbourne, Australia, 2003.
40. Andreu Mas-Colell, Michael Whinston, and Jerry R. Green. Microeconomic Theory. Oxford University Press, 1995.
41. Eric S Maskin and John Riley. Optimal multi-unit auctions. In Frank Hahn, editor, The Economics of Missing Markets, Information, and Games, chapter 14, pages 312-335. Clarendon Press, Oxford, 1989.
42. Roger Myerson. Optimal auction design. Mathematics of Operation Research, 6:58-73, 1981.
43. Roger Myerson and Mark Satterthwaite. Efficient mechanisms for bilateral exchange. Journal of Economic Theory, 28:265-281, 1983.
44. Noam Nisan and Amir Ronen. Algorithmic mechanism design. Games and Economic Behavior, 35:166-196, 2001. Early version in STOC-99.
45. David C Parkes and Lyle Ungar. Iterative combinatorial auctions: Theory and practice. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 74-81, Austin, TX, August 2000.
46. Tuomas Sandholm. An implementation of the contract net protocol based on marginal cost calculations. In Proceedings of the National Conference on Artificial Intelligence (AAAI), pages 256-262, Washington, D.C., July 1993.
47. Tuomas Sandholm. Negotiation among Self-Interested Computationally Limited Agents. PhD thesis, University of Massachusetts, Amherst, 1996. Available at http:// www.cs.cmu.edu/~sandholm/dissertation.ps.
48. Tuomas Sandholm. Issues in computational Vickrey auctions. International Journal of Electronic Commerce, 4(3):107-129, 2000. Special Issue on Applying Intelligent Agents for Electronic Commerce.
49. A short, early version appeared at the Second International Conference on Multi-Agent Systems (ICMAS), pages 299-306, 1996.
50. Tuomas Sandholm and Andrew Gilpin. Sequences of take-it-or-leave-it offers: Near-optimal auctions without full valuation revelation. In AAMAS workshop on Agent-Mediated Electronic Commerce (AMEC V), Melbourne, Australia, 2003.
51. M A Satterthwaite. Strategy-proofness and Arrow's conditions: existence and correspondence theorems for voting procedures and social welfare functions. Journal of Economic Theory, 10:187-217, 1975.
52. W Vickrey. Counterspeculation, auctions, and competitive sealed tenders. Journal of Finance, 16:8-37, 1961.
53. Rakesh V. Vohra. Research problems in combinatorial auctions. Mimeo, version Oct. 29, 2001.
54. Peter R Wurman and Michael P Wellman. AkBA: A progressive, anonymousprice combinatorial auction. In Proceedings of the ACM Conference on Electronic Commerce (ACM-EC), pages 21-29, Minneapolis, MN, October 2000.
55. Makoto Yokoo. The characterization of strategy/false-name proof combinatorial auction protocols: Price-oriented, rationing-free protocol. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI), Acapulco, Mexico, August 2003.
56. Martin Zinkevich, Avrim Blum, and Tuomas Sandholm. On polynomial-time preference elicitation with value queries. In Proceedings of the ACM Conference on Electronic Commerce (ACM-EC), pages 176-185, San Diego, CA, 2003.