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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.  ... 

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

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 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.  ... 

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.  ... 

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.  ...  Reinforcement Learning Model Tran and Cohen [32] have buying agents use reinforcement learning to determine with which selling agents to do business, in order to maximize the buyers' expected profit.  ... 
doi:10.4067/s0718-18762011000300005 fatcat:hjvgyk75tzg75o5psnwgfxhuwq

Self-adaptive filtering using pid feedback controller in electronic commerce

Zeinab Noorian, Mohsen Mohkami, Julita Vassileva
2014 Proceedings of the 25th ACM conference on Hypertext and social media - HT '14  
For example, a variation in the delivered Quality of Services (QoS) can frustrate buyers and they leave the e-marketplace, causing revenue loss.  ...  The performance of e-marketplaces plays a crucial role in attracting and retaining buyers.  ...  Consumers adopt reinforcement learning approach to model the trustworthiness of super-agents.  ... 
doi:10.1145/2631775.2631821 dblp:conf/ht/NoorianMV14 fatcat:rxllxwcxsncu5ffxtentwmpmgu

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  ...  Phase II includes reputation computation using reinforcement learning.  ... 
doi:10.1007/978-3-642-22714-1_30 fatcat:x3fmc5tjtbahpa6sjko5dkz3xa

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.  ...  Our study provides the basis for deciding which approach is most appropriate to employ, in which scenario.  ...  Introducing innovation to the design of trust modeling systems used in agent-oriented e-marketplaces is a crucial concern, as part of the ongoing effort to promote electronic commerce to businesses and  ... 
doi:10.1109/pst.2008.16 dblp:conf/pst/ZhangSC08 fatcat:r5hfc64f3nefhce6doggsrhkla

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  ...  Phase II includes reputation computation using reinforcement learning.  ... 
arXiv:1110.3961v1 fatcat:7nitzirkufcg5dv6yz7dztgrne

Evaluating Reputation Systems for Agent Mediated e-Commerce [article]

Vibha Gaur, Neeraj Kumar Sharma, Punam Bedi
2013 arXiv   pre-print
sharing for inter-agent cooperation and also associates the reputation of an agent with the value of a transaction so that the market approaches an equilibrium state and dishonest agents are weeded out  ...  This paper evaluates various reputation systems for assigning reputation rating to software agents acting on behalf of buyers and sellers in e-market.  ...  Various reputation models [1, 15] described in the literature are based on reinforcement learning.  ... 
arXiv:1303.7377v1 fatcat:vr3qmc4ywrfoxppxovw4bjvx6a

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
This paper provides a dynamic approach to compute the aggregated shared reputation component by filtering out unfair advice and then generating the aggregated shared reputation value.  ...  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.  ...  This paper utilises Reinforcement learning (RL) for modeling the reputation of advisors.  ... 
arXiv:1201.3835v1 fatcat:ciyk6sgwovd2fdo7wj2eto7y5y

Reputation [chapter]

Francesca Giardini, Rosaria Conte, Mario Paolucci
2013 Understanding Complex Systems  
Abstract In this chapter, the role of reputation as a distributed instrument for social order is addressed.  ...  A short review of the state of the art will show the role of reputation in promoting (a) social control in cooperative contexts -like social groups and subgroups -and (b) partner selection in competitive  ...  A conference aiming to propose a scientific approach to Reputation has been organized in 2009: the first International Conference on Reputation, ICORE 2009.  ... 
doi:10.1007/978-3-540-93813-2_15 fatcat:whw6daaeprhp3p3u4md6w7dqme

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

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.  ...  It will explore possible synergies between the reputation techniques and the learning and recommendation approaches used in ONE.  ... 
doi:10.1109/dest.2007.371968 fatcat:3eoc3ucfcrainath4cs7dwitfa
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