Learning User Preferences in a Multiagent System
| Autor: | Joël Quinqueton, Adorjan Kiss |
|---|---|
| Přispěvatelé: | Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM) |
| Jazyk: | angličtina |
| Rok vydání: | 2001 |
| Předmět: |
Preference learning
Computer science business.industry Active learning (machine learning) Multi-agent system Machine Learn Method 05 social sciences Context (language use) 0102 computer and information sciences Machine learning computer.software_genre 01 natural sciences Robot learning Preference Inductive transfer 010201 computation theory & mathematics Conceptual graph 0501 psychology and cognitive sciences [INFO]Computer Science [cs] Artificial intelligence business computer 050107 human factors |
| Zdroj: | 2nd International Workshop of Central and Eastern Europe on Multi-Agent Systems CEEMAS: Central and Eastern Europe on Multi-Agent Systems CEEMAS: Central and Eastern Europe on Multi-Agent Systems, Sep 2001, Cracow, Poland. pp.169-178, ⟨10.1007/3-540-45941-3_18⟩ From Theory to Practice in Multi-Agent Systems ISBN: 9783540433705 CEEMAS |
| DOI: | 10.1007/3-540-45941-3_18⟩ |
| Popis: | International audience; We present in this paper some attempts to design a Machine Learning method to predict preference knowledge in a multi-agents context. This approach is applied to a corporate knowledge management system. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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