NAAS: Negotiation Automation Architecture with Buyer’s Behavior Pattern Prediction Component

Mukhopadhyay, Debajyoti; Vij, Sheetal; Tasare, Suyog

doi:10.1007/978-3-642-31513-8_44

Cited by 9 publications

(5 citation statements)

References 5 publications

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“…We can improve performance of negotiation by adopting the environment conditions. The quality of an opponent model can be measured by using agent's performance as a benchmark or directly evaluating its accuracy by using similarity measures [12].…”

Section: Linear Programmingmentioning

confidence: 99%

An Approach on Multilateral Automated Negotiation

Patrikar¹,

Vij²,

Mukhopadhyay³

2015

Procedia Computer Science

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In E-commerce, numbers of transactions are increasing day by day in B2B and B2C trade. Online negotiation is possible because of automated negotiation. In this paper, we propose linear programming and pattern matching based multilateral automated negotiation system and study some multilateral system with several methods. We have studied fuzzy inference logic based system, multithreading based automated negotiation system, linear programming based system and genetic algorithm based system and we have compared some methods of automated negotiation. Multilateral negotiation system gives better result to participant than bilateral automated negotiation. Technique of pattern matching based automated negotiation gives fast result and reduces overhead of calculation. © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of organizing committee of the 4th International Conference on Advances in Computing, Communication and Control (ICAC3'15).

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Section: Linear Programmingmentioning

confidence: 99%

An Approach on Multilateral Automated Negotiation

Patrikar¹,

Vij²,

Mukhopadhyay³

2015

Procedia Computer Science

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“…Both consumers and providers agents can enter into on exit the environment freely at any time in such type of environment. There was no central controller so that agents were negotiating with each other for allocation of task based on local uses [13].…”

Section: Literature Reviewmentioning

confidence: 99%

“…From equation (9) we can get, (11) (12) Since, (13) Overall negotiation parameter is, (14) Buyer can set its negotiation parameter to calculate counter offer according to equation (9) at each round of negotiation.…”

Section: Figure 7: Agent Mechanismmentioning

confidence: 99%

Adaptive Negotiation Strategies

Pandey¹,

Kumar²,

Tiwari³

2017

IJCA

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Adaptive negotiation strategies are the strategies that are used in the adaptive negotiation model. There are mainly three adaptive negotiation strategies Conceder, Constant, Boulware. These strategies depend upon the utility function and time deadline. The Adaptive negotiation strategies describes the behaviour of the buyer or the nature of the buyer. The nature of buyer depends on the experiences which are taken from seller's offered price. After observing the past experiences the buyer will negotiate the price and the negotiation takes place. General TermsNegotiation refers to a mutual agreement by both seller and buyer for purchasing of a product.Agent is defined as a set of instructions, algorithms or information's which performs actions or gives the output according to the input.

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“…recently proposed related solutions in negotiation over the Internet for efficient E-Commerce and negotiation prediction. [11] [12] 4 Proposed System…”

Section: Technical Literature Surveymentioning

confidence: 99%

Agent Based Negotiation Using Cloud – An Approach in E-Commerce

More¹,

Vij²,

Mukhopadhyay

2014

ICT and Critical Infrastructure: Proceedings of the 48th Annual Convention of Computer Society of India- Vol I

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Cloud computing' allows subscription based access to computing. It also allows storage services over Internet. Automated Negotiation is becoming an emerging, and important area in the field of Multi-Agent Systems in E-Commerce. Multi-Agent based negotiation system is necessary to increase the efficiency of E-negotiation process. Cloud computing provides security and privacy to the user data and low maintenance costs. We propose a Negotiation system using cloud. In this system, all product information and multiple agent details are stored on cloud. Both parties select their agents through cloud for negotiation. Agent acts as a negotiator. Agents have user's details and their requirements for a particular product. Using user's requirement, agents negotiate on some issues such as price, volume, duration, quality and so on. After completing negotiation process, agents give feedback to the user about whether negotiation is successful or not. This negotiation system is dynamic in nature and increases the agents with the increase in participating user.

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NAAS: Negotiation Automation Architecture with Buyer’s Behavior Pattern Prediction Component

Cited by 9 publications

References 5 publications

An Approach on Multilateral Automated Negotiation

An Approach on Multilateral Automated Negotiation

Adaptive Negotiation Strategies

Agent Based Negotiation Using Cloud – An Approach in E-Commerce

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