By Vincent Conitzer, Tuomas Sandholm (auth.), Peyman Faratin, Juan A. Rodríguez-Aguilar (eds.)
This ebook constitutes the completely refereed post-proceedings of the sixth foreign Workshop on Agent-Mediated digital trade, AMEC 2006, held in big apple, manhattan, united states in July 2004 as a part of AAMAS 2004.
The 15 revised complete papers awarded have been conscientiously chosen from 39 submissions in the course of rounds of reviewing and revision. The papers collect novel paintings from such various fields as desktop technology, Operations study, man made Intelligence and dispensed structures that target modeling, implementation and overview of computational buying and selling establishment and/or agent concepts over a various set of products. they're equipped in topical sections on mechanism layout, buying and selling brokers, and tools.
Read Online or Download Agent-Mediated Electronic Commerce VI. Theories for and Engineering of Distributed Mechanisms and Systems: AAMAS 2004 Workshop, AMEC 2004, New York, NY, USA, July 19, 2004, Revised Selected Papers PDF
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Additional info for Agent-Mediated Electronic Commerce VI. Theories for and Engineering of Distributed Mechanisms and Systems: AAMAS 2004 Workshop, AMEC 2004, New York, NY, USA, July 19, 2004, Revised Selected Papers
Since it is not known a priori what beneﬁts manipulation can bring in a particular case, such a mechanism places a burden on agents who need to evaluate potential manipulations for possible gains. The dAGVA mechanism ([3,1]) is an example of a mechanism that is Paretoeﬃcient, incentive-compatible, and budget balanced and individually rational on average. However, it requires a-priori knowledge of the true probability distributions of the agent’s preferences, which is rarely available in practice.
In this case, each agent perceives a particular signal xi that determines the market proﬁtability of the spectrum licenses. Table 1 shows the valuations of player 1 and 2 for each allocation as well as the sum of their valuations. Table 1. 5x1 + 3x2 (∅, AB) 0 x1 + 4x2 x1 + 4x2 We shall now consider how agent 1 views the mechanism as it reports its signal x1 . The explanation for agent 2 is the same and is therefore omitted. Figure 1 shows how the value of each allocation varies for agents 1, 2 and the set of agents I, as agent 1’s reported signal x1 is increased.
Maskin. Efﬁcient auctions. Quarterly Journal of Economics, 115:341 388, 2000. 5. R. K. Dash, D. C. Parkes, and N. R. Jennings. Computational mechanism design: A call to arms. IEEE Intelligent Systems, 18(6):4047, 2003. 6. P. Jehiel and B. Moldovanu. Efﬁcient design with interdependent valuations. Econometrica, 69(5):123759, 2001. 7. V. Krishna. Auction Theory. Academic Press, 2002. 8. C. Mezzetti. Mechanism design with interdependent valuations: Efﬁciency and full surplus extraction. Technical report, University of North Carolina, February 2003.
Agent-Mediated Electronic Commerce VI. Theories for and Engineering of Distributed Mechanisms and Systems: AAMAS 2004 Workshop, AMEC 2004, New York, NY, USA, July 19, 2004, Revised Selected Papers by Vincent Conitzer, Tuomas Sandholm (auth.), Peyman Faratin, Juan A. Rodríguez-Aguilar (eds.)