Paper Info
Title
Appraisal Variance Estimation in the ART Testbed using Fuzzy Corrective Contextual Filters
Abstract
Trust modelling is widely recognized as an aspect of essential importance in the construction of agents and multi agent systems (MAS). As a consequence, several trust formalisms have been developed over the last years. All of them have, in our opinion a limitation: they can determine the trustworthiness or untrustworthiness of the assertions expressed by a given agent, but they don't supply mechanisms for correcting this information in order to extract some utility from it. In order to overcome this limitation, we introduce the concept of reliability as a generalization of trust, and present Fuzzy Contextual Corrective Filters (FCCF) as reliability modeling methods loosely based on system identification and signal processing techniques. In order to prove their usefulness, we study their applicability to the appraisal variance estimation problem in the Agent Reputation and Trust (ART) testbed.
Year
Venue
Keywords
2007
CCIA
last year,multi agent system,present fuzzy contextual corrective,reliability modeling method,trust formalisms,signal processing technique,essential importance,trust modelling,appraisal variance estimation problem,fuzzy corrective contextual filters,appraisal variance estimation,agent reputation,multi agent systems,trust
Field
DocType
Volume
Signal processing,Computer science,Fuzzy logic,Testbed,Multi-agent system,Artificial intelligence,System identification,Rotation formalisms in three dimensions,Valuation (finance),Machine learning,Reputation
Conference
163
ISSN
Citations 
PageRank 
0922-6389
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Esteve del Acebo17611.10
Nicolás Hormazábal273.88
Josep Lluís De La Rosa326041.38