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How to Build up Recommender Agents, Step by Step
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Author(s): Josep Lluis de la Rosa (University of Girona and Easy Innova, Spain), Albert Trias (University of Girona, Spain), Nicolás Hormazábal (University of Girona and Easy Innova, Spain), Esteve del Acebo (University of Girona, Spain)and Miquel Montaner (University of Girona and Strategic Attention Management,Spain)
Copyright: 2011
Pages: 25
Source title:
Multi-Agent Systems for Education and Interactive Entertainment: Design, Use and Experience
Source Author(s)/Editor(s): Martin Beer (Sheffield Hallam University, UK), Maria Fasli (University of Essex, UK)and Debbie Richards (Macquarie University, Australia)
DOI: 10.4018/978-1-60960-080-8.ch013
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Abstract
This chapter proposes a novel educational approach to agents, emphasizing the hand-on practical application of agents, the direct implementation of agency features without any strict methodology, boost the students’ excitement through competition while enhancing the necessary students’ cooperative skills through the development of auction market places. This chapter introduces, step by step, the agency features necessary to construct a recommender agent: user profiling and recommender systems, trust, aggregation-consensus, and negotiation-auctions. Following the aim of hands-on priority, other more advanced topics, such as e-Institutions, multi-agent architectures, and agent programming languages, are intentionally not covered in this chapter, though covered for more specialized courses. The contents of this chapter were developed for the “Tecnologia Agent (TA)” master course in the years 2005-2010 with post-graduate students at the University of Girona, who demonstrated high levels of achievement by grasping a way of building up agents, less concerned of methodologies and more focused on mastering the agent features necessary to build up agents that autonomously work on behalf of users.
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