{"id":"W4377018773","doi":"10.32473/flairs.36.133317","title":"Evaluation of Techniques for Sim2Real Reinforcement Learning","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ... International Florida Artificial Intelligence Research Society Conference","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Reinforcement learning; Computer science; Bridging (networking); Bridge (graph theory); Generalization; Noise (video); Domain (mathematical analysis); Human–computer interaction; Transfer of learning; Process (computing); Artificial intelligence; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005848438,0.00120764,0.0007687734,0.0008203737,0.0005390255,0.0008935959,0.00262421,0.001437116,0.002931347],"category_scores_gemma":[0.01298637,0.000415013,0.0005343151,0.0005189807,0.001105518,0.001392223,0.001701382,0.00141121,0.0006370664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001959383,"about_ca_system_score_gemma":0.001315509,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004506418,"about_ca_topic_score_gemma":0.003762133,"domain_scores_codex":[0.9969755,0.001344981,0.0002009855,0.0004719082,0.0007407754,0.0002658289],"domain_scores_gemma":[0.9915819,0.005168289,0.0004437659,0.001206476,0.001310241,0.0002894505],"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":[0.0008839319,0.000872548,0.002790639,0.0004223166,0.0001114798,0.00009392251,0.0001612733,0.8414201,0.004299598,0.00547519,0.001526103,0.1419429],"study_design_scores_gemma":[0.00006205021,0.0002369126,0.000254779,0.000009954087,0.000007419447,0.00002207156,0.00002236493,0.9940376,0.003944613,0.0006585622,0.0007363114,0.0000074013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2857092,0.001009764,0.69193,0.0005504204,0.0002461055,0.0007466574,0.000316072,0.007504613,0.01198718],"genre_scores_gemma":[0.7585954,0.0001719403,0.2383425,0.0001247214,0.00002157539,0.0003549735,0.0003622737,0.0002285651,0.00179797],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005848438,"threshold_uncertainty_score":0.03092986,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2601722272290781,"score_gpt":0.4271582699048349,"score_spread":0.1669860426757567,"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."}}