Negotiation by Software Agents in Electronic Business: An Example of Hybrid Negotiation

Negotiation by Software Agents in Electronic Business: An Example of Hybrid Negotiation

Nosheen Riaz (Government College University, Pakistan) and Moez Rehman (Government College University, Pakistan)
DOI: 10.4018/978-1-4666-4026-9.ch017
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Abstract

Electronic negotiation is one of many applications that software agents can perform to facilitate electronic business. Negotiations between software agents and humans (hybrid negotiation), can make electronic business efficient and intelligent. It can save time, effort and other valueable resources by replacing the human in electronic business activities and many other domains. However, to enable hybrid negotiation, a software agent needs clear machine interpretable semantics to understand and generate natural language content. Although it is not simple to make natural language content understandable by software agents as a whole, it can be achieved in different domains--in this case electronic business. For this purpose, an example of hybrid negotiation is presented, in which a software agent and a human agent negotiate for a business contract. Problems involved in this negotiation process are partially resolved through ontologies (the main Semantic Web technology), NSS (negotiation support system) and hand written rules.
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Background

The Web has rapidly progressed since its start. The Internet System Consortium advertised nearly 100 million hosts on DNS in January 2000. In January 2012, the amount has increased to 1 billion, and each host maintains from tens to millions of webpages (www.isc.org). Human limited ability is a resistance to search the information of interest from this massive collection. The thousands of webpages come as result against a search query. Because main search tools for today’s web such as Yahoo and Google are Keyword-based (Antoniou & Harmelen, 2008). Many problems occur with keyword based searches including “high recall, low precision”, “low or no recall,” among others. Moreover, results are single webpages, in the case when information is spread over various documents and a separate query is needed to access each document. A human user cannot screen all the webpages to choose a page containing the required content. Machines can be involved for a solution; obviously, machines can process millions of pages within seconds. But the question is, how do machines behave like they understand Web content (Chou, 2007)? Most of today’s Web content is only appropriate for human utilization (Antoniou & Harmelen, 2008). An alternative approach is to represent the Web content in a form that is machine-processable and to use intelligent techniques (e.g., intelligent agents) to take advantage of these representations. This plan of revolutionizing the Web is the Semantic Web initiative (Antoniou & Harmelen, 2008).

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