An Agent-Based Architecture for Personalized Recommendations

Amel Ben Othmane 1 Andrea G. B. Tettamanzi 1 Serena Villata 1 Nhan Le Thanh 1 Michel Buffa 1
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : This paper proposes a design framework for a personalized multi-agent recommender system. More precisely, the proposed framework is a multi-context based recommender system that takes into account user preferences to generate a plan satisfying those preferences. Agents in this framework have a Belief-Desire-Intention (BDI) component based on the well-known BDI architecture. These BDI agents are empowered with cognitive capabilities in order to interact with others agents. They are also able to adapt to the environment changes and to the information coming from other agents. The architecture includes also a planning module based on ontologies in order to represent and reason about plans and intentions. The applicability of the proposed model is shown through a simulation in the NetLogo environment.
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Amel Ben Othmane, Andrea G. B. Tettamanzi, Serena Villata, Nhan Le Thanh, Michel Buffa. An Agent-Based Architecture for Personalized Recommendations. H. Jaap van den Herik; Joaquim Filipe. Agents and Artificial Intelligence. ICAART 2016, 10162, Springer, pp.96 - 113, 2017, Lecture Notes in Computer Science, ⟨10.1007/978-3-319-53354-4_6⟩. ⟨hal-01531141⟩

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