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How to Build up Recommender Agents, Step by Step

How to Build up Recommender Agents, Step by Step

Josep Lluis de la Rosa, Albert Trias, Nicolás Hormazábal, Esteve del Acebo, Miquel Montaner
Copyright: © 2011 |Pages: 25
ISBN13: 9781609600808|ISBN10: 1609600800|EISBN13: 9781609600822
DOI: 10.4018/978-1-60960-080-8.ch013
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MLA

Lluis de la Rosa, Josep, et al. "How to Build up Recommender Agents, Step by Step." Multi-Agent Systems for Education and Interactive Entertainment: Design, Use and Experience, edited by Martin Beer, et al., IGI Global, 2011, pp. 248-272. https://doi.org/10.4018/978-1-60960-080-8.ch013

APA

Lluis de la Rosa, J., Trias, A., Hormazábal, N., del Acebo, E., & Montaner, M. (2011). How to Build up Recommender Agents, Step by Step. In M. Beer, M. Fasli, & D. Richards (Eds.), Multi-Agent Systems for Education and Interactive Entertainment: Design, Use and Experience (pp. 248-272). IGI Global. https://doi.org/10.4018/978-1-60960-080-8.ch013

Chicago

Lluis de la Rosa, Josep, et al. "How to Build up Recommender Agents, Step by Step." In Multi-Agent Systems for Education and Interactive Entertainment: Design, Use and Experience, edited by Martin Beer, Maria Fasli, and Debbie Richards, 248-272. Hershey, PA: IGI Global, 2011. https://doi.org/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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