By Peyman Faratin, Juan A. Rodríguez-Aguilar
This e-book constitutes the completely refereed post-proceedings of the sixth overseas Workshop on Agent-Mediated digital trade, AMEC 2006, held in ny, big apple, united states in July 2004 as a part of AAMAS 2004.
The 15 revised complete papers provided have been rigorously chosen from 39 submissions in the course of rounds of reviewing and revision. The papers collect novel paintings from such varied fields as desktop technology, Operations learn, man made Intelligence and allotted platforms that concentrate on modeling, implementation and overview of computational buying and selling establishment and/or agent innovations over a various set of products. they're prepared in topical sections on mechanism layout, buying and selling brokers, and instruments.
Read or Download Agent-Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems, AAMAS 2004 Workshop, Amec 2004, New York, 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,
Sample text
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.
We have seen that allowing for interdependent valuations comes at the cost of additional computational complexity on the centre. We intend to investigate methods to reduce this load, by reducing the space of allocations that need to be considered when computing the payments to the agents (as discussed in section 5). Our aim is to achieve a mechanism whose complexity is no greater than that of performing the task of winner determination in the underlying auction. Mason and anonymous reviewers for helpful comments.
K. Dash, A. R. Jennings intuitively explaining why the mechanism has the aforementioned properties. We then consider the computational properties of the mechanism, showing that the mechanism does not impose any added complexity on the agents’ bidding process compared to what it would already face in an independent value scenario. However, it does increase the complexity of calculating the payment, a computational load borne by the centre. 1 Economic Properties Proposition 1. The mechanism is incentive-compatible in ex-post Nash Equilibrium.