| Título: | Capturing reputation features in multiagent systems through emerging patterns |
| Autores: |
Grandinetti, Walter M. Chesñevar, Carlos Iván |
| Fecha: |
2012-09-19 2005-05 2005 |
| Publicador: | Unversidad Nacional de La Plata |
| Fuente: |
 |
| Tipo: |
Objeto de conferencia Objeto de conferencia |
| Tema: |
Capturing Reputation Features Emerging Patterns ARTIFICIAL INTELLIGENCE Multiagent systems Ciencias Informáticas |
| Descripción: |
Multiagent systems and online communities rely on rating systems to infer the reputation given to an individual within a particular context. The notion of reputation is essential for helping a given individual to trust in other individuals and for being himself reliable to others. Current techniques for computing individual’s reputations are solely based on recent activities, facilitating a variety of possible attacks. Moreover, the amount of trust each agent has for a given context is based just on his or her reputation. In this paper we outline a new way to thwart reputation-based attacks and to detect trends in behavioral patterns based on historical data by means of knowledge discovery techniques, particularly those existing for emerging patterns. Eje: Inteligencia artificial |
| Idioma: | Inglés |
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