Multiagent Truth Maintenance Applied to a Tourism Recommender System

Multiagent Truth Maintenance Applied to a Tourism Recommender System

Fabiana Lorenzi (Universidade Federal do Rio Grande do Sul (UFRGS), Brasil Universidade Luterana do Brasil, Brazil), Ana L.C. Bazzan (Universidade Federal do Rio Grande do Sul (UFRGS), Brasil) and Mara Abel (Universidade Federal do Rio Grande do Sul (UFRGS), Brazil)
DOI: 10.4018/978-1-60566-818-5.ch004

Abstract

This chapter presents a multiagent recommender system applied to the tourism domain. The multiagent approach is able to deal with distributed expert knowledge to support travel agents in recommending tourism packages. Agents work as experts cooperating and communicating with each other, exchanging information to make the best recommendation possible considering the travelers’ preferences. Each agent has a truth maintenance system component that helps the agents to assume information during the recommendation process as well as to keep the integrity of their knowledge bases. The authors have validated the system via simulations where agents collaborate to recommend travel packages to the user and specialize in some of the tasks available. The experiments show that specialization is useful for the efficacy of the system.
Chapter Preview
Top

Background

This section introduces the fundamental concepts underpinning the technologies applied in our research, and used later in this chapter.

Complete Chapter List

Search this Book:
Reset