An Efficient E-Negotiation Agent Using Rule-Based and Case-Based Approaches

An Efficient E-Negotiation Agent Using Rule-Based and Case-Based Approaches

Amruta More (Maharashtra Institute of Technology, India), Sheetal Vij (Maharashtra Institute of Technology, India) and Debajyoti Mukhopadhyay (Maharashtra Institute of Technology, India)
DOI: 10.4018/978-1-4666-9624-2.ch045
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The research in the area of automated negotiation systems is going on in many universities. This research is mainly focused on making a practically feasible, faster and reliable E-negotiation system. The ongoing work in this area is happening in the laboratories of the universities mainly for training and research purpose. There are number of negotiation systems such as Henry, Kasbaah, Bazaar, Auction Bot, Inspire, Magnet. Our research is based on making an agent software for E-negotiation which will give faster results and also is secure and flexible. Cloud Computing provides security and flexibility to the user data. Using these features we propose an E-negotiation system, in which, all product information and agent details are stored on the cloud. This system proposes three conditions for making successful negotiation. First rule based, where agent will check user requirements with rule based data. Second case based, where an agent will see case based data to check any similar previous negotiation case is matching to the user requirement. Third bilateral negotiation model, if both rules based data and case based data are not matching with the user requirement, then agent use bilateral negotiation model for negotiation. After completing negotiation process, agents give feedback to the user about whether negotiation is successful or not. Using rule based reasoning and case based reasoning this system will improve the efficiency and success rate of the negotiation process.
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In this section, we are presenting literature survey related to rule based and cased reasoning. In previous paper (More, Vij and Mukhopadhyay, 2013), we have referred ten papers related to automated negotiation for literature survey.

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