{"id":"W1595275443","doi":"10.1007/11780519_18","title":"An Online POMDP Algorithm Used by the PoliceForce Agents in the RoboCupRescue Simulation","year":2006,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Partially observable Markov decision process; Computer science; Action (physics); Algorithm; Artificial intelligence; Mathematical optimization; Machine learning; Markov chain; Markov model; 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":[0.00053336,0.0007017797,0.001000064,0.0003507708,0.001018762,0.0008605911,0.001269338,0.001046859,0.005437986],"category_scores_gemma":[0.001323125,0.0004436099,0.0005664031,0.0003511236,0.000535165,0.0007411403,0.001214867,0.0009634812,0.0005678842],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00078946,"about_ca_system_score_gemma":0.001751985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01272128,"about_ca_topic_score_gemma":0.01425582,"domain_scores_codex":[0.9997589,0.00007460333,0.00001212694,0.00005176797,0.00005476799,0.00004773643],"domain_scores_gemma":[0.9996737,0.0001612119,0.00001764767,0.00004581477,0.00006848642,0.00003310915],"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":[0.00009919539,0.00005047433,0.0002210616,0.00003968646,0.00001825371,0.00005839271,0.00004343568,0.9521343,0.0007548162,0.01720273,0.001023998,0.02835356],"study_design_scores_gemma":[0.0000237794,0.0000133785,0.00002137681,0.000004013405,0.000004000894,0.00000552461,0.0000065123,0.9962007,0.0003716875,0.00272948,0.0006161452,0.000003365006],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02495525,0.0001015799,0.9601844,0.0002102945,0.0001187265,0.0001446317,0.0001552981,0.001259131,0.0128706],"genre_scores_gemma":[0.5106756,0.0001132923,0.4833427,0.00007630945,0.00002141477,0.000321053,0.0002468863,0.0001812468,0.005021375],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01272128,"threshold_uncertainty_score":0.02529442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02001175732201941,"score_gpt":0.256155839688626,"score_spread":0.2361440823666066,"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."}}