Developing trust in recommender agents

ABSTRACT

Trust is one of the most important social concepts that helps human agents to cope with their social environment and is present in all human interaction. Like in real world, agents should rely in some agents and mistrust in other ones to achieve a purpose. In this paper we develop a model of trust in the collaborative world as a new approach of recommender agents development. Mainly, we provide recommender agents with a technology to look for similar agents that advice him. The model presented comprehends the evolution of trust, that is, trust dynamics. Moreover, the model proposed emphasizes proactiveness since the agent looks for other agents in a lack for information situation instead of remaining passive or providing either a negative or empty answer to the user.

REFERENCES

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Information filtering

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Retrieval models

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems
      I.2.6 Learning
          Subjects: Parameter learning

General Terms:
Theory

Keywords:
opinion-based filtering, recommender agents, trust