{"id":"W12582432","doi":"","title":"Evolution of recurrent neural networks to control Autonomous Life Agents","year":2001,"lang":"en","type":"article","venue":"Genetic and Evolutionary Computation Conference","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brock University; University of Waterloo","funders":"","keywords":"Artificial life; Recurrent neural network; Autonomous agent; Computer science; Artificial intelligence; Task (project management); Artificial neural network; Intelligent agent; Multi-agent system; Control (management); Simple (philosophy); Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001262482,0.0001779932,0.0002123642,0.0001601393,0.0002540887,0.00005443156,0.0003781439,0.00007183351,0.00002701711],"category_scores_gemma":[0.00003095244,0.0001898881,0.00005499172,0.0005454213,0.00009499425,0.0002386407,0.0001614835,0.0001090163,0.00002117644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009082415,"about_ca_system_score_gemma":0.0001990489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006603816,"about_ca_topic_score_gemma":0.00000522945,"domain_scores_codex":[0.9984123,0.0000988715,0.0004488281,0.000475303,0.0002725514,0.0002921399],"domain_scores_gemma":[0.9988317,0.00009732656,0.0001660853,0.000273861,0.0003594777,0.0002715192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003163281,0.0002021754,0.01297408,0.00001451934,0.00003020702,0.000004647381,0.0002644816,0.8487435,0.00006931769,0.04113149,0.002611524,0.09392244],"study_design_scores_gemma":[0.0003235575,0.0001181289,0.3245724,0.00001176755,0.000008471487,0.00003458895,0.00002782164,0.6703406,7.738379e-7,0.003892071,0.0005358112,0.0001340371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09909128,0.0008442595,0.8973489,0.001728878,0.0002953796,0.0003722013,0.00001118134,0.00009742607,0.0002104247],"genre_scores_gemma":[0.9476522,0.00008028369,0.05175132,0.0002644354,0.0001124491,0.00005961566,0.0000151157,0.000007139804,0.00005746801],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8485609,"threshold_uncertainty_score":0.7743412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02028320403609548,"score_gpt":0.2507493733689903,"score_spread":0.2304661693328948,"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."}}