An Electronic Marketplace Based on Reputation and Learning
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| Format: | Artículo científico |
| Language: | en |
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Universidad de Talca
2007
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| _version_ | 1876430714282442752 |
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| author | Omid Roozmand |
| author_facet | Omid Roozmand |
| contents | An Electronic Marketplace Based on Reputation and Learning Omid Roozmand Mohammad Ali Nematbakhsh Ahmad Baraani Multidisciplinaria (Ciencias Naturales y Exactas) Reputation Reinforcement Learning Electronic Commerce Agents In this paper, we propose a market model which is based on reputation and reinforcement learningalgorithms for buying and selling agents. Three important factors: quality, price and delivery-time are considered in the model. We take into account the fact that buying agents can have different priorities on quality, price and delivery-time of their goods and selling agents adjust their bids according to buying agents preferences. Also we have assumed that multiple selling agents may offer the same goods with different qualities, prices anddelivery-times. In our model, selling agents learn to maximize their expected profits by using reinforcementlearning to adjust product quality, price and delivery-time. Also each selling agent models the reputation ofbuying agents based on their profits for that seller and uses this reputation to consider discount for reputable buying agents. Buying agents learn to model the reputation of selling agents based on different features ofgoods: reputation on quality, reputation on price and reputation on delivery-time to avoid interaction withdisreputable selling agents. The model has been implemented with Aglet and tested in a large-sized marketplace. The results show that selling/buying agents that model the reputation of buying/selling agentsobtain more satisfaction rather than selling/buying agents who only use the reinforcement learning. 2007 artículo científico 0718-1876 https://www.redalyc.org/articulo.oa?id=96520102 en http://www.redalyc.org/revista.oa?id=965 Journal of Theoretical and Applied Electronic Commerce Research application/pdf Universidad de Talca Journal of Theoretical and Applied Electronic Commerce Research (Chile) Num.1 Vol.2 |
| format | Artículo científico |
| id | redalyc_96520102 |
| institution | Redalyc |
| language | en |
| publishDate | 2007 |
| publisher | Universidad de Talca |
| spellingShingle | An Electronic Marketplace Based on Reputation and Learning Omid Roozmand Multidisciplinaria (Ciencias Naturales y Exactas) Reputation Reinforcement Learning Electronic Commerce Agents An Electronic Marketplace Based on Reputation and Learning Omid Roozmand Mohammad Ali Nematbakhsh Ahmad Baraani Multidisciplinaria (Ciencias Naturales y Exactas) Reputation Reinforcement Learning Electronic Commerce Agents In this paper, we propose a market model which is based on reputation and reinforcement learningalgorithms for buying and selling agents. Three important factors: quality, price and delivery-time are considered in the model. We take into account the fact that buying agents can have different priorities on quality, price and delivery-time of their goods and selling agents adjust their bids according to buying agents preferences. Also we have assumed that multiple selling agents may offer the same goods with different qualities, prices anddelivery-times. In our model, selling agents learn to maximize their expected profits by using reinforcementlearning to adjust product quality, price and delivery-time. Also each selling agent models the reputation ofbuying agents based on their profits for that seller and uses this reputation to consider discount for reputable buying agents. Buying agents learn to model the reputation of selling agents based on different features ofgoods: reputation on quality, reputation on price and reputation on delivery-time to avoid interaction withdisreputable selling agents. The model has been implemented with Aglet and tested in a large-sized marketplace. The results show that selling/buying agents that model the reputation of buying/selling agentsobtain more satisfaction rather than selling/buying agents who only use the reinforcement learning. 2007 artículo científico 0718-1876 https://www.redalyc.org/articulo.oa?id=96520102 en http://www.redalyc.org/revista.oa?id=965 Journal of Theoretical and Applied Electronic Commerce Research application/pdf Universidad de Talca Journal of Theoretical and Applied Electronic Commerce Research (Chile) Num.1 Vol.2 |
| title | An Electronic Marketplace Based on Reputation and Learning |
| topic | Multidisciplinaria (Ciencias Naturales y Exactas) Reputation Reinforcement Learning Electronic Commerce Agents |
| url | https://www.redalyc.org/articulo.oa?id=96520102 |