{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mira-a-computational-neuro-based-cognitive","title":"MIRA: A Computational Neuro-Based Cognitive Architecture Applied to Movie Recommender Systems","arxiv_id":"1902.09291","date":"2019-02-25","proceeding":null,"authors":["Mariana B. Santos","Amanda M. Lima","Lucas A. Silva","Felipe S. Vargas","Guilherme A. Wachs-Lopes","Paulo S. Rodrigues"],"abstract":"The human mind is still an unknown process of neuroscience in many aspects.\nNevertheless, for decades the scientific community has proposed computational\nmodels that try to simulate their parts, specific applications, or their\nbehavior in different situations. The most complete model in this line is\nundoubtedly the LIDA model, proposed by Stan Franklin with the aim of serving\nas a generic computational architecture for several applications. The present\nproject is inspired by the LIDA model to apply it to the process of movie\nrecommendation, the model called MIRA (Movie Intelligent Recommender Agent)\npresented percentages of precision similar to a traditional model when\nsubmitted to the same assay conditions. Moreover, the proposed model reinforced\nthe precision indexes when submitted to tests with volunteers, proving once\nagain its performance as a cognitive model, when executed with small data\nvolumes. Considering that the proposed model achieved a similar behavior to the\ntraditional models under conditions expected to be similar for natural systems,\nit can be said that MIRA reinforces the applicability of LIDA as a path to be\nfollowed for the study and generation of computational agents inspired by\nneural behaviors.","url_abs":"http://arxiv.org/abs/1902.09291v2","url_pdf":"http://arxiv.org/pdf/1902.09291v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mira-a-computational-neuro-based-cognitive","repo_url":"https://github.com/VisaoComputacional/mira","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"movie-recommendation","task_name":"Movie Recommendation"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"},{"task_slug":"small-data","task_name":"Small Data Image Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}