{"id":"W2111609065","doi":"10.1109/icinfa.2009.5205107","title":"A non-time based action executor for the coordinated hybrid agent framework","year":2009,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Executor; Control engineering; Computer science; Automation; Teleoperation; Robot; Control (management); Multi-agent system; Mobile robot; Action (physics); Engineering; Artificial intelligence","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":[0.001150339,0.0006717565,0.0004968254,0.000407415,0.0004083303,0.0008597869,0.001570656,0.0005756343,0.001990449],"category_scores_gemma":[0.001319367,0.0002577718,0.0005341888,0.0001927914,0.0008927669,0.001020001,0.0007831429,0.001320341,0.0004317146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000494332,"about_ca_system_score_gemma":0.001404644,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001873437,"about_ca_topic_score_gemma":0.002195998,"domain_scores_codex":[0.9992667,0.0001833442,0.00006320551,0.0001357007,0.0002907223,0.00006022002],"domain_scores_gemma":[0.9990626,0.0003479609,0.0001368214,0.0001579645,0.0002173413,0.00007725694],"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":[0.0007174999,0.000314658,0.001793066,0.0005237585,0.0002058881,0.001127796,0.000841354,0.3387942,0.07630342,0.2917094,0.004359603,0.2833094],"study_design_scores_gemma":[0.00006893148,0.0002415661,0.0001749206,0.00002291808,0.00004771567,0.0001766889,0.00003044166,0.9666964,0.01410516,0.009089121,0.009310948,0.00003517823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005381403,0.0001325379,0.9919177,0.00006561716,0.00005506938,0.00008013541,0.00001489819,0.0006693614,0.001683305],"genre_scores_gemma":[0.3984527,0.0002605051,0.5960392,0.0001182669,0.00009631547,0.0003520548,0.0001040103,0.0001247635,0.004452114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001990449,"threshold_uncertainty_score":0.006658673,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0266239154481717,"score_gpt":0.2867016735602264,"score_spread":0.2600777581120547,"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."}}