By Sofia Ceppi, Nicola Gatti (auth.), Esther David, Enrico Gerding, David Sarne, Onn Shehory (eds.)
This quantity includes 18 completely refereed and revised papers detailing fresh advances in study on designing buying and selling brokers and mechanisms for agent-mediated e-commerce. They have been initially offered 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 facets, all within the context of e-commerce functions like buying and selling, auctions, or negotiations. They mix ways from assorted fields of arithmetic, desktop technology, and economics akin to man made intelligence, dispensed platforms, operations examine, and online game thought.
Read 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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Additional info 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
In: Proc. of 8th Int. Conf. on Autonomous Agents and Multiagent Systems, AAMAS 2009 (2009) 3. : Efficient design with interdependent valuations. Econometrica 69, 1237–1259 (2001) 4. : Incentives for expressing opinions in online polls. In: Procedings of the 9th ACM Conference on Electronic Commerce, pp. 119–128 (2008) 5. : Mechanism design with interdependent valuations: Efficiency. Econometrica 72(5), 1617–1626 (2004) Eliciting Expert Advice in Service-Oriented Computing 43 6. : Eliciting informative feedback: The peer-prediction method.
Mechanisms for information elicitation. Artificial Intelligence 172(16-17), 1917–1939 (2008) Approximating the Qualitative Vickrey Auction by a Negotiation Protocol Koen V. nl Abstract. A result of Bulow and Klemperer has suggested that auctions may be a better tool to obtain an eﬃcient outcome than negotiation. For example, some auction mechanisms can be shown to be eﬃcient and strategy-proof. However, they generally also require that the preferences of at least one side of the auction are publicly known.
In our setting, we want agents to report predictions on multiple service providers, only one of which is actually chosen and observed. H. Gerding, K. R. Jennings agree with predictions of other agents . 3. 2 Marginal Contribution Scoring Rule Based on Reality In this section we introduce a scoring rule which rewards agents according to the informativeness of the information they provide, given the reports of other agents. Our marginal-contribution rule is given by: P oSk∗ (ω) P oSk∗ (ω−i ) 1 − P oSk∗ (ω) 1 − P oSk∗ (ω−i ) τi (ω|success) = αi ln τi (ω|f ail) = αi ln , (7) , if k ∗ = ∅, and τi = 0 otherwise (if no provider is selected), where αi > 0 is a scaling parameter.