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Autonomous Agents and Multi-Agent Systems

Erschienen in:

01.11.2014

Trust-oriented buyer strategies for seller reporting and selection in competitive electronic marketplaces

verfasst von: Zeinab Noorian, Jie Zhang, Yuan Liu, Stephen Marsh, Michael Fleming

Erschienen in: Autonomous Agents and Multi-Agent Systems | Ausgabe 6/2014

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Abstract

In competitive electronic marketplaces where some selling agents may be dishonest and quality products offered by good sellers are limited, selecting the most profitable sellers as transaction partners is challenging, especially when buying agents lack personal experience with sellers. Reputation systems help buyers to select sellers by aggregating seller information reported by other buyers (called advisers). However, in such competitive marketplaces, buyers may also be concerned about the possibility of losing business opportunities with good sellers if they report truthful seller information. In this paper, we propose a trust-oriented mechanism built on a game theoretic basis for buyers to: (1) determine an optimal seller reporting strategy, by modeling the trustworthiness (competency and willingness) of advisers in reporting seller information; (2) discover sellers who maximize their profit by modeling the trustworthiness of sellers and considering the buyers’ preferences on product quality. Experimental results confirm that competitive marketplaces operating with our mechanism lead to better profit for buyers and create incentives for seller honesty.

Vorheriger Artikel Multi-agent systems with reinforcement hierarchical neuro-fuzzy models

Nächster Artikel Automated agents for reward determination for human work in crowdsourcing applications

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\(R\) is not necessarily equal to \(\mathbf{R}\) but in the experiments of this paper we assume that they are the same. The model can also be applied to the case where the value of \(R\) is different for each buyer.

Table 2

Prisoner’s dilemma payoff matrix

	Cooperate		Defect
	Agent 1	Agent 2	Agent 1	Agent 2
Cooperate	R	R	K	T
Defect	T	K	P	P

Here, we choose a set of sellers \(S \subset \{s_1,\ldots ,s_m\}\) with whom buyer \(b\) has sufficient experience, to make sure that the buyer has sufficient knowledge to judge the advisers.

We notice that a trust-aware FSBP auction model is not an application but an extension built on the previous work.

In [6] each quality attribute \(i\) is characterized with a particular coefficient, which is identical for all sellers. In our model, we consider all coefficients as \(1\).

The buyers adopting the ALLC and ALLD strategies only model the competency of advisers, that is \(T_r(a_i) = C_o(a_i)\).

That is the reason why we only show one figure to present the profit of sellers in different types of environments.

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Titel: Trust-oriented buyer strategies for seller reporting and selection in competitive electronic marketplaces
verfasst von: Zeinab Noorian
Jie Zhang
Yuan Liu
Stephen Marsh
Michael Fleming
Publikationsdatum: 01.11.2014
Verlag: Springer US
Erschienen in: Autonomous Agents and Multi-Agent Systems / Ausgabe 6/2014
Print ISSN: 1387-2532
Elektronische ISSN: 1573-7454
DOI: https://doi.org/10.1007/s10458-013-9243-z

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