{"id":"W4408954824","doi":"10.1007/s00521-025-11100-0","title":"Advances and applications in inverse reinforcement learning: a comprehensive review","year":2025,"lang":"en","type":"review","venue":"Neural Computing and Applications","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"RUDN University; Monash University","keywords":"Computational Science and Engineering; Computer science; Reinforcement learning; Reinforcement; Inverse; Artificial intelligence; Machine learning; Applied mathematics; Mathematics; Geometry; Engineering; Structural 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002037827,0.0004125631,0.001036733,0.000273494,0.0004046538,0.0001563708,0.0007206402,0.0001264588,0.000001798121],"category_scores_gemma":[0.00005181328,0.0003763205,0.0001306866,0.001187468,0.0001101036,0.0001666115,0.0008274371,0.0007261074,0.0000122938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006319176,"about_ca_system_score_gemma":0.0001175318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008436875,"about_ca_topic_score_gemma":0.000001283223,"domain_scores_codex":[0.9976979,0.0001804194,0.0008106328,0.0007742105,0.0002092893,0.0003275819],"domain_scores_gemma":[0.9977801,0.0008350654,0.0005344808,0.0006384854,0.00009541095,0.000116453],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[1.819814e-7,0.00001036069,0.00001490595,0.0371617,0.00001293911,8.105666e-7,0.00002940838,0.02043149,4.572716e-8,0.005698108,0.0001020059,0.936538],"study_design_scores_gemma":[0.00009770482,0.00002818413,0.000004588491,0.01200743,0.0001057978,0.00001636348,0.00001478532,0.04592859,5.998701e-8,0.00007487462,0.9414251,0.000296481],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[1.299346e-7,0.6834531,0.3135853,0.00007456933,0.00002963257,0.001756033,0.000001022402,0.0001302712,0.0009699182],"genre_scores_gemma":[0.00002005861,0.9958057,0.002747573,0.0003061039,0.00006448301,0.0006234812,0.00008623333,0.00001614526,0.0003301611],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9413232,"threshold_uncertainty_score":0.9998689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03519127845833417,"score_gpt":0.3449301907153309,"score_spread":0.3097389122569968,"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."}}