{"id":"W2967250176","doi":"10.1613/jair.1.11635","title":"Autonomous Target Search with Multiple Coordinated UAVs","year":2019,"lang":"en","type":"article","venue":"Journal of Artificial Intelligence Research","topic":"Constraint Satisfaction and Optimization","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Royal Holloway, University of London; Engineering and Physical Sciences Research Council; Massachusetts Institute of Technology","keywords":"Submodular set function; Computer science; Greedy algorithm; Exploit; Scalability; Mathematical optimization; Constraint (computer-aided design); Heuristic; Limit (mathematics); Greedy randomized adaptive search procedure; Property (philosophy); Artificial intelligence; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005207937,0.000540499,0.0007144453,0.0004087835,0.0005319215,0.0008471964,0.0009809168,0.0008161651,0.001408327],"category_scores_gemma":[0.00159361,0.000351443,0.0004680057,0.0008623937,0.0005830453,0.0008946536,0.000998333,0.000610847,0.0002191884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006826934,"about_ca_system_score_gemma":0.001077058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009322102,"about_ca_topic_score_gemma":0.006039716,"domain_scores_codex":[0.9995647,0.0001411992,0.00002008826,0.0001095251,0.0000916472,0.00007279737],"domain_scores_gemma":[0.9993141,0.0003922531,0.00009135112,0.00006830734,0.00007120745,0.00006272145],"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":[0.00009024136,0.0000332196,0.0005155345,0.00003168138,0.00003398022,0.0001293746,0.00004587861,0.9696456,0.002775601,0.007030921,0.0005853005,0.01908269],"study_design_scores_gemma":[0.00001546707,0.00003692753,0.0000915352,0.00000224792,0.000005264489,0.00002100947,0.00002471016,0.995981,0.0006373547,0.002678308,0.000502752,0.000003429813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1542435,0.0003407914,0.8367048,0.0003682786,0.00004468075,0.00008393428,0.0001256203,0.0005618567,0.007526551],"genre_scores_gemma":[0.8602023,0.0001734323,0.1369547,0.00008290458,0.00001785341,0.0001156268,0.0001071382,0.00003496668,0.002311113],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009322102,"threshold_uncertainty_score":0.01853567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07474897448577872,"score_gpt":0.3541518828374389,"score_spread":0.2794029083516602,"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."}}