{"id":"W4388134984","doi":"10.1007/978-981-99-3814-8_4","title":"Evolutionary Computation and the Reinforcement Learning Problem","year":2023,"lang":"en","type":"book-chapter","venue":"Genetic and evolutionary computation","topic":"Evolutionary Algorithms and Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Reinforcement learning; Computer science; Artificial intelligence; Observability; Population; Adaptation (eye); Action selection; Evolutionary computation; Evolutionary robotics; Selection (genetic algorithm); Natural selection; Task (project management); Machine learning; Engineering; Mathematics; Agency (philosophy); Biology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003513693,0.0003998453,0.0003519566,0.000254033,0.001166357,0.0001510725,0.00031847,0.000232881,0.00001263557],"category_scores_gemma":[0.00001850002,0.0003518563,0.0001149152,0.0001908478,0.0004880383,0.0002728403,0.0005573906,0.0004472324,0.0001440377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001362966,"about_ca_system_score_gemma":0.0001846308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004143586,"about_ca_topic_score_gemma":0.000002888121,"domain_scores_codex":[0.9975516,0.0001024046,0.0006484015,0.000789255,0.0005876486,0.0003206523],"domain_scores_gemma":[0.9984682,0.0004337388,0.0004095226,0.0002720945,0.0002814236,0.0001350152],"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":[0.00002590871,0.00001810582,0.00003891958,0.00006943835,0.0001162843,0.000007307347,0.0004156703,0.3231543,0.000002683139,0.6241591,0.008087571,0.04390472],"study_design_scores_gemma":[0.0007140595,0.00008751027,0.004986458,0.00007179086,0.00005178807,0.0001168254,0.00002504748,0.6377324,1.201218e-7,0.3460229,0.009892142,0.0002989269],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00008696481,0.004845541,0.9566172,0.003619357,0.0003168394,0.001187938,0.0000123539,0.0004579875,0.03285578],"genre_scores_gemma":[0.1241208,0.01258271,0.4658605,0.0008471538,0.001501076,0.0007202566,0.001884705,0.0002568475,0.392226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4907567,"threshold_uncertainty_score":0.9998934,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01465560192987431,"score_gpt":0.2238490074227482,"score_spread":0.2091934054928739,"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."}}