{"id":"W7124317441","doi":"10.65109/ltgs2519","title":"Be Considerate: Avoiding Negative Side Effects in Reinforcement Learning","year":2022,"lang":"","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute","funders":"","keywords":"Reinforcement learning; Agency (philosophy); Reinforcement; Control (management); Action (physics); Discretion","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","sts","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003502513,0.0007155155,0.0008038353,0.0008033225,0.002861433,0.0008675394,0.00156739,0.0001401271,0.001618976],"category_scores_gemma":[0.002366806,0.0008423391,0.0001908277,0.002248418,0.0002015557,0.001128529,0.004694565,0.004065994,0.0001789303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001505869,"about_ca_system_score_gemma":0.0007488346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005287341,"about_ca_topic_score_gemma":0.00002446314,"domain_scores_codex":[0.9906412,0.002913177,0.00150713,0.001347746,0.001939631,0.00165111],"domain_scores_gemma":[0.9941061,0.003645427,0.0007985655,0.0009660033,0.000170755,0.0003131889],"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":[0.00005003851,0.00006109346,0.001064705,0.0001208015,0.00008853246,0.0003986719,0.01358373,0.9370049,0.0006155797,0.0439546,0.0006150808,0.002442328],"study_design_scores_gemma":[0.002376796,0.00201921,0.0004240454,0.0001572738,0.00003222366,0.00005547675,0.00361513,0.9824513,0.002753106,0.0005765324,0.004608112,0.0009307708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007137528,0.0002207519,0.9189725,0.002262352,0.002397187,0.001628111,6.037689e-7,0.0003067865,0.06707419],"genre_scores_gemma":[0.963586,0.0000637466,0.006859848,0.003138145,0.00008401846,0.0001992946,0.00001104953,0.00006121953,0.02599668],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9564485,"threshold_uncertainty_score":0.9994028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02380526822181108,"score_gpt":0.2594788744108522,"score_spread":0.2356736061890411,"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."}}