{"id":"W3102849613","doi":"10.48550/arxiv.2011.03125","title":"LBGP: Learning Based Goal Planning for Autonomous Following in Front","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Trajectory; Planner; Computer science; Robot; Reinforcement learning; Artificial intelligence; Front (military); Deep learning; Human–computer interaction; Simulation; 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":[0.0005165405,0.0007020517,0.0005652162,0.0002400171,0.0003410381,0.0005215229,0.001562337,0.001102185,0.004011598],"category_scores_gemma":[0.001105776,0.0004207575,0.0003853844,0.0002112133,0.0007184278,0.0008984553,0.00136987,0.001391079,0.001319366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006080304,"about_ca_system_score_gemma":0.001174742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007085497,"about_ca_topic_score_gemma":0.006767661,"domain_scores_codex":[0.9998373,0.00003451797,0.000007271337,0.00005160152,0.00003720942,0.00003209403],"domain_scores_gemma":[0.9997509,0.00009060671,0.00002462635,0.00005069806,0.00004397513,0.00003910475],"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":[0.000351221,0.0003291674,0.00142751,0.000156148,0.00006309339,0.0002800061,0.0001802986,0.7030072,0.01235169,0.01146289,0.01007992,0.2603109],"study_design_scores_gemma":[0.00001367764,0.00004196582,0.00008190073,0.000006192155,0.000003909528,0.00001949845,0.000007284211,0.9940546,0.00146233,0.003245665,0.001058617,0.000004313111],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01848819,0.0001759432,0.9719678,0.0001907827,0.00007040753,0.00008082553,0.0001067139,0.006008129,0.002911224],"genre_scores_gemma":[0.6654155,0.0001759546,0.3258653,0.0002550436,0.00003334362,0.0001868733,0.0003499147,0.0003316944,0.007386369],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007085497,"threshold_uncertainty_score":0.01408851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08554689636773007,"score_gpt":0.2142208071226572,"score_spread":0.1286739107549271,"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."}}