ECA Rule-based negotiation agent in e-commerce

2005

The note reports on the current status of an implementation of a rule-based negotiation mechanism in a model e-commerce multi-agent system. Here, we briefly describe the conceptual architecture of the system and its initial implementation utilizing JADE and JESS. A particular negotiation scenario involving English auctions performed in parallel is also discussed.

2015

E-commerce is considered a key service within modern information society, and the idea of automating e-commerce transactions has attracted much interest in recent years. A multi-agent model is a system that applies various autonomous agents to accomplish specified goals. Such a system addresses resource allocation issues. Because the nature of resource trading requires multiple agents to request geographically dispersed heterogeneous resources, we use a multi-agent architecture for e-commerce because each agent can be describe each participant intelligently. In this paper, negotiation agents based on fuzzy ECA rule-based proposed. Here we focus on agents in e-commerce that negotiate between sellers and buyers in order to get the best deal. The negotiation process between buyers and its sellers begins through combined and fairness protocols. We add learning properties to agents based on a fuzzy decision tree to develop negotiation skills and present the results. Using a fuzzy decisio...

2004

Nowadays, many researches are being been made for the development of new transaction system in an effort to transform current off-line system into on-line one. However, these researches mainly focuses on ordinary commercial transaction system, i.e. the one that supports fixed price transaction, in which consumers usually ought to buy goods at the price offered by sellers. Accordingly, more studies are to be made for the system to support both buyers and sellers in searching the proper price level through negotiations. Under current e-commerce environment, an automated negotiation system is badly needed to respond quickly and flexibly to the diverse environmental changes and also to perform many negotiations consistently and effectively. To this end, this paper has developed a multi-agent based automated negotiation system. This new system creates multi-issue negotiation proposals automatically, evaluating the counterpart's proposal, and then, if necessary, preparing and sending counter proposals time and again, and finally accepting or rejecting.

Advanced Research on Cloud Computing Design and Applications, 2015

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.

INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences, 2011

To automate most of commerce time-consuming stages of the buying process, software agent's technologies have been proposed and employed in different transaction stages of e-commerce. The agents in e-negotiation dialogs based on their owner requirements until reaching agreement on one or multi issues of the negotiation. In addition, in many real conditions negotiation, negotiation agents have only limited information about their opponents and bounded rationality. Therefore, using heuristic algorithm to develop negotiation agents' decision-making mechanism is useful. For this propose, we proposed framework of intelligent agent based interactive recommendation and automated negotiation system in B2C e-commerce, so we expect that the negotiation time and transaction cost are reduced.

In this work we discus the process of multi-agent negotiations by means of electronic auctions and present possible approaches for finding effective solutions to the problem of resource allocation. We focus our attention on:-Centralized auction types (classic auctions, continuous double auction-CDA, etc.) – Effective allocation depends on bidding strategies. We implement new software for modeling e-auctions and propose a new methodology for evaluating bidding strategies.-Decentralized auction types (combinatorial auctions) – Auction effectiveness depends on the quality of the algorithm for winner determination. We design new heuristics for winner determination in single-and multi-item combinatorial auctions. First chapter describes the theoretical foundations of agent-based negotiations. Second chapter elaborates on MASECA (Multi-Agent Software for Electronic Commerce Auctions) and its functions as CDA-simulator. Third chapter suggests a methodology for comparison between bidding ag...

International Journal of Engineering Research and, 2016

Online or E-Shopping requires a great effort of investigation to find the best deal. Although immense information is available on World Wide Web to make smart decision in shopping, however for analyzing, comparing, and making purchase decision in e-business transaction, humans are required. Most of the developed E-Commerce businesses are still based on human intelligence. To save this investigation cum effort time, we can automate this task using some software agents which will automate this e-commerce shopping. Not just automation, we can also put the negotiation capabilities into the software agent which can help us to get the best available deal. Software agents help to automate the process of buying and selling goods and services in E-Market. To enhance the shopping process agents are the useful tools and acts as a channel between traditional market and automated E-market. This paper presents usage of negotiation protocols and intelligent agent negotiation strategies which have been mentioned in literature, responsible for price negotiation. The conclusion here is to work in automating ecommerce transaction(s) using improved negotiation strategies to enhance the experience of e-business by reducing the human effort.

Journal of Software Engineering and Applications, 2015

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, 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 partners 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-negotiation 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 negotiation 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 negotiation 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, S. R. Vij et al. 522 rule based data, and case based data will be stored on the cloud. So that system automatically becomes flexible. We also compare E-negotiation agent automated negotiation and behavior prediction system to prove that using rule based and case based approaches system should become fast.

2006 Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, 2006

In our recent work we have established that to develop an extensible agent-based e-commerce system it is necessary to logically separate the negotiation process from other parts of the system. This note deals with the design of the "negotiation box"-the component that actually runs the negotiation processes. Furthermore, interaction of the negotiation box with the rest of the system is addressed.