MIRA: A Computational Neuro-Based Cognitive Architecture Applied to
  Movie Recommender Systems
  The human mind is still an unknown process of neuroscience in many aspects.
Nevertheless, for decades the scientific community has proposed computational
models that try to simulate their parts, specific applications, or their
behavior in different situations. The most complete model in this line is
undoubtedly the LIDA model, proposed by Stan Franklin with the aim of serving
as a generic computational architecture for several applications. The present
project is inspired by the LIDA model to apply it to the process of movie
recommendation, the model called MIRA (Movie Intelligent Recommender Agent)
presented percentages of precision similar to a traditional model when
submitted to the same assay conditions. Moreover, the proposed model reinforced
the precision indexes when submitted to tests with volunteers, proving once
again its performance as a cognitive model, when executed with small data
volumes. Considering that the proposed model achieved a similar behavior to the
traditional 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 be
followed for the study and generation of computational agents inspired by
neural behaviors.
