By Sofia Ceppi, Nicola Gatti (auth.), Esther David, Enrico Gerding, David Sarne, Onn Shehory (eds.)
This quantity comprises 18 completely refereed and revised papers detailing contemporary advances in examine on designing buying and selling brokers and mechanisms for agent-mediated e-commerce. They have been initially awarded on the eleventh overseas Workshop on Agent-Mediated digital trade (AMEC 2009) collocated with AAMAS 2009 in Budapest, Hungary, or the 2009 Workshop on buying and selling Agent layout and research (TADA 2009) collocated with IJCAI 2009 in Pasadena, CA, united states. The papers specialise in issues equivalent to person agent habit and agent interplay, collective habit, mechanism layout, and computational elements, all within the context of e-commerce functions like buying and selling, auctions, or negotiations. They mix methods from diversified fields of arithmetic, laptop technological know-how, and economics corresponding to synthetic intelligence, allotted platforms, operations study, and video game conception.
Read Online or Download Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets: AAMAS Workshop, AMEC 2009, Budapest, Hungary, May 12, 2009, and IJCAI Workshop, TADA 2009, Pasadena, CA, USA, July 13, 2009, Selected and Revised Paper PDF
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Extra resources for Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets: AAMAS Workshop, AMEC 2009, Budapest, Hungary, May 12, 2009, and IJCAI Workshop, TADA 2009, Pasadena, CA, USA, July 13, 2009, Selected and Revised Paper
Finally, we discuss some more challenges that remain to be addressed. The remainder of the paper is structured as follows. We first present the problem and the desirable properties of the payment rules more formally in Section 2, and then apply Eliciting Expert Advice in Service-Oriented Computing 31 the mechanism design approach to achieve truthful revelation in Section 3. We also show that the mechanism design approach does not induce effort and suggest instead the scoring rule approach in Section 4.
Nevertheless, this approach is still not foolproof, as an expert can sometimes still profit by manipulating the outcome by simply reducing the reported variance (by proportionally increasing the number of reported successes and failures) whilst keeping the probability of success the same. As we have seen, this will not affect the score obtained through peer prediction. Although not perfect, however, the combination does reduce the number of cases in which a deviation from truth telling is profitable.
Furthermore, an expert is scored based only on the result of the selected outcome, and its remaining observations are not rewarded. g. by making other outcomes less attractive. We note, however, that this is only a problem when there is a relatively large imbalance in the number of observations from each provider. A possible solution to the above problem is to produce a transfer which combines the marginal contribution scoring rule with one of the other two approaches. We discuss each of the two combinations in more detail, starting with the peer prediction method.
Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets: AAMAS Workshop, AMEC 2009, Budapest, Hungary, May 12, 2009, and IJCAI Workshop, TADA 2009, Pasadena, CA, USA, July 13, 2009, Selected and Revised Paper by Sofia Ceppi, Nicola Gatti (auth.), Esther David, Enrico Gerding, David Sarne, Onn Shehory (eds.)