Strategies for Agent-Based Negotiation in E-Trade

Strategies for Agent-Based Negotiation in E-Trade

Raja Al-Jaljouli (Deakin University, Australia) and Jemal H. Abawajy (Deakin University, Australia)
DOI: 10.4018/978-1-4666-1888-6.ch003
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Abstract

E-negotiation handles negotiation over the Internet without human supervision and has shown effectiveness in concluding verifiable and more favorable agreements in a reasonably short time. In this chapter, the authors discuss the negotiation system and its components with particular emphasis on negotiation strategies. A negotiation strategy defines strategic tactics, which advise on the proper action to select from a set of possible actions that optimizes negotiation outcomes. A strategy should integrate negotiation goals and reactive attitudes. Usually, a fixed strategy is implemented during the course of negotiation regardless of significant decision-making factors including market status, opponent’s profile, or eagerness for a negotiated goods/service. The chapter presents the main negotiation strategies and outlines the different decision-making factors that should be considered. A strategy uses a utility function to evaluate the offer of an opponent and advises on the generation of a counter offer or the best interaction. The authors finally discuss different utility functions presented in the literature.
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Introduction

Negotiation is a process in which two or more parties have conflicting requirements in terms of goals and demands and try to reach mutual agreement through concession or change in requirements (Pruitt, 1981). E-negotiation refers to negotiation conducted over the Internet and has been proposed to facilitate negotiation and generate better outcomes. It is an automated process that tries to optimize utilities of negotiating entities through iteration. It facilitates negotiation through the Internet as being free from place and time constraints. It also saves negotiators time and effort they usually spend in trying to reach an agreement.

E-negotiation is a hot research topic and represents a strategic stage in e-commerce (Sandholm, 1999). It manages beliefs and goals of interacting parties, and tries to resolve conflicts through concessions and search for affordable and acceptable alternatives (Calisti, 2002). It overcomes limitations of human negotiation that suffers from emotional, rational, or superficial responses. It also keeps a record of negotiation traces for later verification or jury cases. Moreover, it offers much broader market search and results in error-free calculations that promote customer satisfaction and trust in E-negotiation.

E-negotiation can be fully automated through the deployment of software intelligent agents. Agents can autonomously carry out negotiation on behalf of negotiating entities. Agents can be stationary or mobile. Agent-mediated negotiation has recently received much attention (Faratin et al., 1998; Kraus & Lehmann, 1995; Fatima et al., 2002, 2004; Luo et al., 2003; Li & Tesauro, 2003; Sandholm, 1999). The implementation of mobile agents in E-negotiation has shown that they are more efficient than stationary agents as they exhibit distinctive characteristics (Chen et al, 2008): (1) ability to reduce network loads; (2) dynamic adaptation to changes in the environment; (3) ability to overcome network latency; (4) asynchronous and autonomous execution. Hence, mobile agents have been recommended for E-negotiation (Faratin et al., 1998; Kraus & Lehmann, 1995).

Negotiation is a vital component of electronic trading. It is the key decision-making approach used to reach consensus between trading partners. Mobile agents have recently been proposed for negotiation in electronic trading applications. Agents are deployed to act on behalf of consumers and vendors roaming the Internet, negotiating their particular requests with various service providers, and making decisions autonomously. They have shown effectiveness in automating human decisions such as concluding verifiable agreements, facilitating global trading, and optimizing clients’ utilities. Moreover, they ensure timely delivery of services/resources, and less resources allocation.

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