{"id":"W2921191538","doi":"10.23919/acc.2019.8814485","title":"Multi-Robot Routing for Persistent Monitoring with Latency Constraints","year":2019,"lang":"en","type":"preprint","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Vertex (graph theory); Latency (audio); Solver; Computer science; Robot; Patrolling; Heuristic; Approximation algorithm; Mathematical optimization; Graph; Algorithm; Mathematics; Theoretical computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004849904,0.0004334234,0.0005073413,0.0001390908,0.0001531641,0.0003843395,0.001604763,0.0002783356,0.000004522532],"category_scores_gemma":[0.00007602052,0.0003585839,0.0002498551,0.000121156,0.00007974116,0.0001883005,0.00112907,0.000577289,0.00005038361],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000171084,"about_ca_system_score_gemma":0.0003752053,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006822071,"about_ca_topic_score_gemma":6.173568e-7,"domain_scores_codex":[0.9973307,0.000050349,0.0004037647,0.001159181,0.0004114406,0.0006446015],"domain_scores_gemma":[0.9978918,0.0002097093,0.0003185353,0.001158744,0.0002646918,0.0001565646],"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":[0.00001792821,0.0002139968,0.03386843,0.0005768653,0.0006221714,0.00009806845,0.004451366,0.9253186,0.0004372557,0.001137565,0.0001479167,0.03310982],"study_design_scores_gemma":[0.000817937,0.0001419851,0.005148534,0.0008031987,0.00004747795,0.00005152961,0.0002507538,0.9916951,0.0003591898,0.0000512129,0.00001675838,0.0006162907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001977847,0.0001118375,0.9919942,0.000259144,0.002959017,0.001031424,0.00001187436,0.000477499,0.001177158],"genre_scores_gemma":[0.2687005,0.000004211502,0.7298569,0.00003153308,0.0001531364,0.00006871844,0.000009100908,0.00002713698,0.001148807],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2667226,"threshold_uncertainty_score":0.9998866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0716275427209212,"score_gpt":0.2947560714199437,"score_spread":0.2231285286990225,"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."}}