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A Reputation-Oriented Reinforcement Learning Strategy for Agents in Electronic Marketplaces

Thomas Tran, Robin Cohen
2002 Computational intelligence  
In this paper, we propose a reputation oriented reinforcement learning algorithm for buying and selling agents in electronic market environments.  ...  We also include the ability for buying agents to optionally explore the marketplace in order to discover new reputable sellers.  ...  In this paper, we propose a reinforcement learning and reputation based algorithm for buying and selling agents in electronic market environments.  ... 
doi:10.1111/1467-8640.t01-1-00203 fatcat:xe4e2g2z2vddpdwfewevs4uzxy

Page 641 of Psychological Abstracts Vol. 90, Issue 2 [page]

2003 Psychological Abstracts  
(U Waterloo, Dept of Comput- er Science, Waterloo, ON, Canada) A reputation-oriented reinforce- ment learning strategy for agents in electronic marketplaces.  ...  —Proposes a reputation-oriented reinforcement learning algorithm for buying and selling agents in electronic market environments.  ... 

Page 1614 of Mathematical Reviews Vol. , Issue 2004b [page]

2004 Mathematical Reviews  
reinforcement learning strategy for agents in electronic marketplaces.  ...  Summary: “In this paper, we propose a reputation-oriented re- inforcement learning algorithm for buying and selling agents in electronic market environments.  ... 

Personality for buyer and seller agents in electronic marketplace based on reputation and reinforcement learning

Adel Jahanbani
2012 African Journal of Business Management  
In this paper, we propose a marketplace model which is based on personality, reputation and reinforcement learning algorithms for buying and selling agents.  ...  In addition, seller agents apply reinforcement learning to establish a model of reputation of buyer agents.  ...  In developing learning algorithms for agents in electronic marketplaces, we use a reputation mechanism, in addition to reinforcement learning, to provide added robustness to buying agents.  ... 
doi:10.5897/ajbm11.2492 fatcat:2edwjacysrcefhjhq3edqcazxq

Page 341 of Psychological Abstracts Vol. 92, Issue 1 [page]

2005 Psychological Abstracts  
In this article, we present an approach for the design of adaptive business agents that uses a combination of reinforcement learning and reputation modeling.  ...  —Adaptive business agents op- erate in electronic marketplaces, learning from past experiences to make ef- fective decisions on behalf of their users.  ... 

A Dynamic Seller Selection Model for an Agent Mediated e-Market [chapter]

Vibha Gaur, Neeraj Kumar Sharma
2011 Communications in Computer and Information Science  
This paper proposes a dynamic reputation framework using reinforcement learning and fuzzy set theory that ensures judicious use of information sharing for inter-agent cooperation.  ...  A dynamic reputation model would provide virtually instantaneous knowledge about the changing e-market environment and would utilise Internets' capacity for continuous interactivity for reputation computation  ...  The reputation computation strategy proposed in this paper uses reinforcement learning (RL) techniques which provide a general framework for sequential decision making problems [10] .  ... 
doi:10.1007/978-3-642-22714-1_30 fatcat:x3fmc5tjtbahpa6sjko5dkz3xa

A Dynamic Framework of Reputation Systems for an Agent Mediated e-market [article]

Vibha Gaur, Neeraj Kumar Sharma
2011 arXiv   pre-print
This paper proposes a dynamic reputation framework using reinforcement learning and fuzzy set theory that ensures judicious use of information sharing for inter-agent cooperation.  ...  A dynamic reputation model would provide virtually instantaneous knowledge about the changing e-market environment and would utilise Internets' capacity for continuous interactivity for reputation computation  ...  The reputation computation strategy proposed in this paper uses reinforcement learning (RL) techniques which provide a general framework for sequential decision making problems [10] .  ... 
arXiv:1110.3961v1 fatcat:7nitzirkufcg5dv6yz7dztgrne

Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems

Jie Zhang
2011 Journal of Theoretical and Applied Electronic Commerce Research  
The unfair rating problem exists when a buying agent models the trustworthiness of selling agents by also relying on ratings of the sellers from other buyers in electronic marketplaces, that is in a reputation  ...  More importantly, in this work, we focus on experimental comparison of our approach with two key models in a simulated dynamic e-marketplace environment.  ...  Inspired by the evaluation in [34] , a marketplace may involve some buyers that have an adaptive lying strategy where buyers may learn from the marketplace and build some strategies to adapt their lying  ... 
doi:10.4067/s0718-18762011000300005 fatcat:hjvgyk75tzg75o5psnwgfxhuwq

A Digital Marketplace for Education [chapter]

Beverly Park Woolf, Victor Lesser, Chris Eliot, Zachary Eyler-Walker, Mark Klein
2002 Electronic Business and Education  
We describe a web-based Educational MarketPlace that matches student requests to available and appropriate resources.  ...  industry of education in which a teacher handcrafts materials fixed by space and time.  ...  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.  ... 
doi:10.1007/978-1-4615-1497-8_1 fatcat:5t2fb7bsfzbcpjsdg35ugpad6q

A Dynamic Model for Sharing Reputation of Sellers among Buyers for Enhancing Trust in Agent Mediated e-market [article]

Vibha Gaur, Neeraj Kumar Sharma, Punam Bedi
2012 arXiv   pre-print
Reputation systems aim to reduce the risk of loss due to untrustworthy participants. This loss is aggravated by dishonest advisors trying to pollute the e-market environment for their self-interest.  ...  It provides incentive to honest advisors in lieu of repeated sharing of honest opinion by increasing the weight of their opinion and by making the increase in the reputation of honest advisors monotonically  ...  This paper utilises Reinforcement learning (RL) for modeling the reputation of advisors.  ... 
arXiv:1201.3835v1 fatcat:ciyk6sgwovd2fdo7wj2eto7y5y

A Detailed Comparison of Probabilistic Approaches for Coping with Unfair Ratings in Trust and Reputation Systems

Jie Zhang, Murat Sensoy, Robin Cohen
2008 2008 Sixth Annual Conference on Privacy, Security and Trust  
Based on the implication of such analysis, we then focus on experimental comparison of our approach with two key models in a framework that simulates a dynamic electronic marketplace environment.  ...  In this paper, we first summarize these approaches and provide a detailed categorization of them. This includes our own "personalized" approach for addressing this problem.  ...  Inspired by the evaluation in [14] , a marketplace may involve some buyers that have an adaptive lying strategy where buyers may learn from the marketplace and build some strategies to adapt their lying  ... 
doi:10.1109/pst.2008.16 dblp:conf/pst/ZhangSC08 fatcat:r5hfc64f3nefhce6doggsrhkla

Open Negotiation Environment: An Open Source Self-Learning Decentralised Negotiation Framework for Digital Ecosystems

Luigi Telesca, Jason Finnegan, Pierfranco Ferronato, Paul Malone, Francesco Ricci, Katarina Stanoevska-Slabeva
2007 2007 Inaugural IEEE-IES Digital EcoSystems and Technologies Conference  
of a single company.  ...  The process of negotiation and contracting of complex services that can be provided in a cooperative manner by member companies of the ecosystem is an essential binding element among them.  ...  In this respect, Machine Learning research in automated negotiation, has focussed on optimization methods to improve an agent bid policy, either based on genetic algorithms or on reinforcement learning  ... 
doi:10.1109/dest.2007.371968 fatcat:3eoc3ucfcrainath4cs7dwitfa

DART: A DISTRIBUTED ANALYSIS OF REPUTATION AND TRUST FRAMEWORK

Amirali Salehi-Abari, Tony White
2012 Computational intelligence  
These vulnerabilities reinforce the need for new evaluation criteria for trust and reputation models called exploitation resistance which reflects the ability of a trust model to be unaffected by agents  ...  Agents require trust and reputation concepts in order to identify communities of agents with which to interact reliably.  ...  Tran and Cohen [54] proposed a marketplace model and learning algorithms for buying and selling agents in electronic marketplaces.  ... 
doi:10.1111/j.1467-8640.2012.00453.x fatcat:y2vghvd4jngw3c7zrhsbcmqtha

A Machine-Learning Approach to Automated Negotiation and Prospects for Electronic Commerce

Jim R. Oliver
1996 Journal of Management Information Systems  
Static agents might also be justified in marketplaces that are relatively static or in cases where the downside of a poor strategy is great.  ...  Finally, when the user has confidence in the strategies available for use by the system, she or he will “field” the agents to the marketplace.  ... 
doi:10.1080/07421222.1996.11518135 fatcat:3f6v47golver5c62sgyxlb6u4a

Market intelligence and price adaptation

Emad Eldeen Elakehal, Julian Padget
2012 Proceedings of the 14th Annual International Conference on Electronic Commerce - ICEC '12  
In the context of e-commerce, it is critical for a retailing com pany to be able to assess the market and respond quickly to changes in competition and/or service levels and availability of its products  ...  offer and operates internationally in a number of market places.  ...  [14] on using reinforcement learning techniques to improve dynamic pricing agents' performance, where they show the effect on the marketplaces and the effect of different adaptive pricing strategies  ... 
doi:10.1145/2346536.2346538 dblp:conf/ACMicec/ElakehalP12 fatcat:bwh7qsilanayjfmco3j32y4l4e
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