{"id":"W2072771680","doi":"10.1115/imece2010-40055","title":"Multi-Robot Cooperative Transportation of Objects Using Modified Q-Learning","year":2010,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Robot; Robustness (evolution); Mobile robot; Computer science; Artificial intelligence; Object (grammar); Robot control; Social robot; Computer vision; Task (project management); Human–computer interaction; Engineering; Systems 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":[0.001727102,0.0007583759,0.001030221,0.0004134609,0.0004588479,0.000652291,0.001753709,0.001003817,0.001070875],"category_scores_gemma":[0.002981982,0.0003711027,0.0005463486,0.0005234448,0.0009532337,0.001069103,0.000984657,0.0008118709,0.0002506397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006686717,"about_ca_system_score_gemma":0.0009079912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003444624,"about_ca_topic_score_gemma":0.001983124,"domain_scores_codex":[0.9992546,0.0002865984,0.00004395619,0.0001509801,0.000189446,0.00007441915],"domain_scores_gemma":[0.9982784,0.0009679815,0.0002127504,0.0001326685,0.0003399998,0.00006815396],"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":[0.0001254844,0.0001535007,0.0007300525,0.00007004344,0.00007010138,0.00008876015,0.0001316281,0.8702513,0.005081727,0.004608036,0.000461869,0.1182275],"study_design_scores_gemma":[0.00001375692,0.00005481546,0.00005876741,0.000001533457,0.000003432615,0.00001046549,0.000004246457,0.9980159,0.0005315519,0.001151247,0.0001506982,0.000003615495],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01295474,0.0000836522,0.9862903,0.00005763468,0.00001443004,0.00005354558,0.000004378871,0.0001500231,0.000391338],"genre_scores_gemma":[0.6491274,0.0001122936,0.3488221,0.0001206601,0.0000335049,0.0002886968,0.00004575726,0.00003810924,0.001411503],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003444624,"threshold_uncertainty_score":0.009133935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03733732766053533,"score_gpt":0.2878889955004935,"score_spread":0.2505516678399582,"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."}}