An Adaptive Trust Model Based on Fuzzy Logic

In cooperative environments is common that agents delegate tasks to each other to achieve their goals since an agent may not have the capabilities or resources to achieve its objectives alone. However, to select good partners, the agent needs to deal with information about the abilities, experience, and goals of their partners. In this situation, the lack or inaccuracy of information may affect the agent's judgment about a given partner; and hence, increases the risk to rely on an untrustworthy agent. Therefore, in this work, we present a trust model that combines different pieces of information, such as social image, reputation, and references to produce more precise information about the characteristics and abilities of agents. An important aspect of our trust model is that it can be easily configured to deal with different evaluation criteria. For instance, as presented in our experiments, the agents are able to select their partners by availability instead of the expertise level. Besides, the model allows the agents to decide when their own opinions about a partner are more relevant than the opinions received from third parties, and vice-versa. Such flexibility can be explored in dynamic scenarios, where the environment and the behavior of the agents might change constantly

A multi-agent systems\' model for knowledge sharing using communitary social networks.

Este trabalho apresenta um modelo para sistemas multiagentes constituídos por agentes de informação destinados a auxiliar comunidades humanas que partilham conhecimento. Tais agentes são cientes do entorno social dos usuários, pois possuem representações do conhecimento dos mesmos e também das redes sociais que os circundam, organizadas subjetivamente. Conceitos pertencentes às suas ontologias são estendidos com informação organizacional para representar de forma explícita as situações nas quais foram aprendidos e utilizados. Discute-se como tais agentes autônomos podem raciocinar sobre o uso e a privacidade de conceitos em termos de construções organizacionais, possibilitando raciocinar sobre papéis sociais em comunidades abertas na Internet.This work presents a model for multi-agent systems for information agents supporting information-sharing communities. Such agents are socially aware in the sense that they have representations of the users\' knowledge and also of their social networks, which are subjectively organized. Concepts in their ontologies are extended with organizational information to record explicitly the situations in which they were learned and used. It is discussed how such autonomous agents are allowed to reason about concept usage and privacy in terms of organizational constructs, paving the way to reason about social roles in open Internet communities

An Adaptive Trust Model Based on Fuzzy Logic

In cooperative environments is common that agents delegate tasks to each other to achieve their goals since an agent may not have the capabilities or resources to achieve its objectives alone. However, to select good partners, the agent needs to deal with information about the abilities, experience, and goals of their partners. In this situation, the lack or inaccuracy of information may affect the agent's judgment about a given partner; and hence, increases the risk to rely on an untrustworthy agent. Therefore, in this work, we present a trust model that combines different pieces of information, such as social image, reputation, and references to produce more precise information about the characteristics and abilities of agents. An important aspect of our trust model is that it can be easily configured to deal with different evaluation criteria. For instance, as presented in our experiments, the agents are able to select their partners by availability instead of the expertise level. Besides, the model allows the agents to decide when their own opinions about a partner are more relevant than the opinions received from third parties, and vice-versa. Such flexibility can be explored in dynamic scenarios, where the environment and the behavior of the agents might change constantly