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The human mind is still an unknown process of neuroscience in many aspects.Nevertheless, for decades the scientific community has proposed computationalmodels that try to simulate their parts, specific applications, or theirbehavior in different situations. The most complete model in this line isundoubtedly the LIDA model, proposed by Stan Franklin with the aim of servingas a generic computational architecture for several applications. The presentproject is inspired by the LIDA model to apply it to the process of movierecommendation, the model called MIRA (Movie Intelligent Recommender Agent)presented percentages of precision similar to a traditional model whensubmitted to the same assay conditions. Moreover, the proposed model reinforcedthe precision indexes when submitted to tests with volunteers, proving onceagain its performance as a cognitive model, when executed with small datavolumes. Considering that the proposed model achieved a similar behavior to thetraditional models under conditions expected to be similar for natural systems,it can be said that MIRA reinforces the applicability of LIDA as a path to befollowed for the study and generation of computational agents inspired byneural behaviors.

MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender Systems