Agent-mediated electronic commerce: automated negotiation by Maria Fasli, Onn Shehory

By Maria Fasli, Onn Shehory

This ebook constitutes the completely refereed post-proceedings of the joint foreign Workshops on buying and selling Agent layout and research, TADA 2006, and on Agent Mediated digital trade, AMEC VIII 2006, held in Hakodate, Japan, in could 2006 as an linked occasion of AAMAS 2006, the fifth foreign Joint convention on self reliant brokers and Multiagent Systems.

The 17 revised complete papers awarded have been conscientiously chosen from the shows made on the workshop and comprise papers from the once a year TAC event whose function is to stimulate examine in buying and selling brokers and industry mechanisms via offering a platform for brokers competing in well-defined industry situations. The papers handle a mixture of either theoretical and functional matters in buying and selling agent layout and applied sciences, theoretical and empirical assessment of thoughts in complicated buying and selling eventualities in addition to mechanism layout. additionally coated are problems with agent-mediated digital trade starting from the layout of digital marketplaces and effective protocols to behavioral elements of brokers working in such environments.

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Extra info for Agent-mediated electronic commerce: automated negotiation and strategy design for electronic markets. AAMAS 2006 workshop, Tada/Amec 2006, Hakodate, Japan, May 9, 2006, selected and revised papers

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All m issues) or reject a complete offer. An agreement can therefore take place either on all the m issues or none of them. As per single-issue negotiation, an agent decides what to offer by backward reasoning. However, since an offer for the PD includes a share for all the m issues, agents can now make tradeoffs across the issues in order to maximise their cumulative utilities. The function TRADEOFFA is agent a’s function for making tradeoffs, and is described in more detail in the proof of Theorem 1.

Unfortunately, we cannot benefit from any previous results in the literature since they do not take into account the novel notion of t-relationship, and thus the generated data set never reflects the relationships among goods. For instance, consider the t2 transformation in figure 1. It is clear that it is unrealistic that a bid offers a motherboard cheaper than some of its components. This fact motivated the need for substantially changing the approach in [7] to coherently introduce t-relationships.

During time period t, either a or b could be the offering agent. Consider the case where a makes an offer at t. The package that a offers at t gives b a cumulative utility of U b ([at+1 , bt+1 ], t + 1). However, since there is more than one issue, there is more than one package that gives b this cumulative utility. On Efficient Procedures for Multi-issue Negotiation 35 Between these packages, a offers the one that maximises its own cumulative utility. m Thus, a’s tradeoff problem is to find a package [at , bt ] that maximises Σc=1 kca atc such m that Σc=1 (δct−1 − atc )kcb = U b ([at+1 , bt+1 ], t + 1) and 0 ≤ atc ≤ 1 for 1 ≤ c ≤ m.

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