{"id":1616,"date":"2023-12-15T16:17:39","date_gmt":"2023-12-15T15:17:39","guid":{"rendered":"https:\/\/babel.isa.uma.es\/kipr\/?p=1616"},"modified":"2023-12-15T16:17:58","modified_gmt":"2023-12-15T15:17:58","slug":"leveraging-the-unexplainability-and-opacity-of-nns-to-generate-random-numbers","status":"publish","type":"post","link":"https:\/\/babel.isa.uma.es\/kipr\/?p=1616","title":{"rendered":"Leveraging the unexplainability and opacity of NNs to generate random numbers"},"content":{"rendered":"<h4>Y. Almardeny, A. Benavoli, N. Boujnah and E. Naredo, <strong>A Reinforcement Learning System for Generating Instantaneous Quality Random Sequences, <\/strong> IEEE Transactions on Artificial Intelligence, vol. 4, no. 3, pp. 402-415, June 2023 <a href=\"https:\/\/doi.org\/10.1109\/TAI.2022.3161893\" target=\"_blank\">DOI: 10.1109\/TAI.2022.3161893<\/a>.<\/h4>\n<blockquote><p>Random numbers are essential to most computer applications. Still, producing high-quality random sequences is a big challenge. Inspired by the success of artificial neural networks and reinforcement learning, we propose a novel and effective end-to-end learning system to generate pseudorandom sequences that operates under the upside-down reinforcement learning framework. It is based on manipulating the generalized information entropy metric to derive commands that instantaneously guide the agent toward the optimal random behavior. Using a wide range of evaluation tests, the proposed approach is compared against three state-of-the-art accredited pseudorandom number generators (PRNGs). The experimental results agree with our theoretical study and show that the proposed framework is a promising candidate for a wide range of applications.<\/p><\/blockquote>\n","protected":false},"excerpt":{"rendered":"<p>Y. Almardeny, A. Benavoli, N. Boujnah and E. Naredo, A Reinforcement Learning System for Generating Instantaneous Quality Random Sequences, IEEE <span class=\"ellipsis\">&hellip;<\/span> <span class=\"more-link-wrap\"><a href=\"https:\/\/babel.isa.uma.es\/kipr\/?p=1616\" class=\"more-link\"><span>Read More &rarr;<\/span><\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[37],"tags":[194,522],"class_list":["post-1616","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","tag-deep-neural-networks","tag-random-number-generation"],"_links":{"self":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1616"}],"collection":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=1616"}],"version-history":[{"count":1,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1616\/revisions"}],"predecessor-version":[{"id":1617,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=\/wp\/v2\/posts\/1616\/revisions\/1617"}],"wp:attachment":[{"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=1616"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=1616"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/babel.isa.uma.es\/kipr\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=1616"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}