{"id":"W4310849374","doi":"10.1016/j.autcon.2022.104691","title":"To imitate or not to imitate: Boosting reinforcement learning-based construction robotic control for long-horizon tasks using virtual demonstrations","year":2022,"lang":"en","type":"article","venue":"Automation in Construction","topic":"Innovations in Concrete and Construction Materials","field":"Engineering","cited_by":56,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Reinforcement learning; Teleoperation; Boosting (machine learning); Robot; Computer science; Artificial intelligence; Adaptability; Control (management); Human–computer interaction; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001674345,0.0008364573,0.0008359394,0.0002277832,0.0002836318,0.0003922756,0.000948226,0.0007525986,0.001422847],"category_scores_gemma":[0.005329836,0.0003431884,0.00028769,0.0001277103,0.0008276823,0.000727569,0.001149765,0.001296206,0.000238204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004100253,"about_ca_system_score_gemma":0.0006386683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002837209,"about_ca_topic_score_gemma":0.002142593,"domain_scores_codex":[0.9996178,0.0001258333,0.0000183827,0.0000904617,0.00007579783,0.00007171809],"domain_scores_gemma":[0.9975646,0.001535702,0.0002380268,0.0001515654,0.0003429097,0.0001671903],"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":[0.0003477254,0.0002581182,0.001168216,0.00007158871,0.00004765658,0.0000530673,0.00006845579,0.9124459,0.006742842,0.001906409,0.0007909071,0.07609907],"study_design_scores_gemma":[0.00001008318,0.00007618978,0.0001222059,0.000003022231,0.000003862935,0.00000584653,0.000002890378,0.9987967,0.0004836707,0.0004350814,0.00005764439,0.000002793343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3160914,0.0006346829,0.6777181,0.0003656319,0.0001477094,0.0001103834,0.00002982836,0.0009079517,0.003994382],"genre_scores_gemma":[0.9833377,0.00004736209,0.01581543,0.00005518928,0.00001227312,0.00003325882,0.00001731897,0.0000200107,0.0006614621],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002837209,"threshold_uncertainty_score":0.008854866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02382609092479164,"score_gpt":0.2690324045061778,"score_spread":0.2452063135813861,"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."}}