{"id":"W2620415937","doi":"10.5430/air.v6n2p57","title":"A proposal of privacy preserving reinforcement learning for secure multiparty computation","year":2017,"lang":"en","type":"article","venue":"Artificial Intelligence Research","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Reinforcement learning; Computation; Encryption; Unsupervised learning; Artificial intelligence; Machine learning; Cloud computing; Supervised learning; Theoretical computer science; Algorithm; Computer security; Artificial neural network","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001457428,0.0005730439,0.000843893,0.0004166357,0.0006925819,0.001116013,0.001729203,0.001299818,0.00443903],"category_scores_gemma":[0.002464907,0.0002828699,0.0009293907,0.0005416571,0.00131575,0.001474527,0.001487026,0.001779833,0.0005914301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001002726,"about_ca_system_score_gemma":0.001351361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001380963,"about_ca_topic_score_gemma":0.000749399,"domain_scores_codex":[0.9989278,0.0004211337,0.00004212609,0.0002420216,0.000250278,0.0001165506],"domain_scores_gemma":[0.9992406,0.0003565599,0.0000711809,0.00009340907,0.0001436752,0.00009447815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001448078,0.0001026326,0.000664697,0.0001792456,0.0000905095,0.000305249,0.0002225881,0.3331524,0.004002867,0.5799546,0.004380364,0.07680009],"study_design_scores_gemma":[0.00003669141,0.00006153945,0.00006440219,0.0000100045,0.00001142574,0.00006961253,0.0000109763,0.9357793,0.0004697083,0.06010805,0.003365988,0.00001240879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003825748,0.0003063596,0.9897198,0.0003851011,0.00008077417,0.00004153114,0.00001926374,0.0001307265,0.00549065],"genre_scores_gemma":[0.714248,0.0009592607,0.2687062,0.00043729,0.0002577237,0.0003280932,0.00007233539,0.00009209934,0.01489895],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00443903,"threshold_uncertainty_score":0.01485002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2207497653687221,"score_gpt":0.4530274687240633,"score_spread":0.2322777033553412,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}