Journal of Software Engineering and Applications, 2015, 8, 521-530 Published Online October 2015 in SciRes. http://www.scirp.org/journal/jsea http://dx.doi.org/10.4236/jsea.2015.810049 How to cite this paper: Vij, S.R., More, A., Mukhopadhyay, D. and Agrawal, A.J. (2015) An E-Negotiation Agent Using Rule Based and Case Based Approaches: A Comparative Study with Bilateral E-Negotiation with Prediction. Journal of Software Engineering and Applications, 8, 521-530. http://dx.doi.org/10.4236/jsea.2015.810049 An E-Negotiation Agent Using Rule Based and Case Based Approaches: A Comparative Study with Bilateral E-Negotiation with Prediction Sheetal R. Vij 1 , Amruta More 1 , Debajyoti Mukhopadhyay 2 , Avinash J. Agrawal 3 1 Department of Computer Engineering, Maharashtra Institute of Technology, Pune, India 2 Department of Information Technology, Maharashtra Institute of Technology, Pune, India 3 Department of Computer Science and Engineering, Ramdeobaba College of Engineering and Management, Nagpur, India Email: sheetal.sh@gmail.com , moreamruta930@gmail.com , debajyoti.mukhopadhyay@gmail.com , agrawalaj@rknec.edu Received 20 August 2015; accepted 9 October 2015; published 12 October 2015 Copyright © 2015 by authors and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ Abstract 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 sys- tem. 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, and Magnet. Our research is based on making an agent software for E-negotiation which will give faster results and also is secure and flexible. The negotiation part- ners and contents between the service providers change frequently. The negotiation process can be transformed into rules and cases. Using these features, a new automated negotiation model for agent integrating rule based and case based reasoning can be derived. We propose an E-negotia- tion system, in which all product information and multiple agent details are stored on the cloud. An E-negotiation agent acts as a negotiator. Agent has user’s details and their requirements for a particular product. It will check rules based data whether any rule is matching with the user requirement. An agent will see case based data to check any similar negotiation case matching to the user requirement. If a case matches with user requirement, then agent will start the nego- tiation process using case based data. If any rule related requirement is found in the rule base data, then agent will start the negotiation process using rule based data. If both rules based data and cases based data are not matching with the user requirement, then agent will start the ne- gotiation process using Bilateral Negotiation model. After completing negotiation process, agent gives feedback to the user about whether negotiation is successful or not. The product details,