{"id":"W4407949057","doi":"10.1109/cdc56724.2024.10886022","title":"Approximate Environment Decompositions for Robot Coverage Planning using Submodular Set Cover","year":2024,"lang":"en","type":"article","venue":"","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Mitacs","keywords":"Submodular set function; Cover (algebra); Set cover problem; Computer science; Set (abstract data type); Robot; Motion planning; Mathematical optimization; Artificial intelligence; Mathematics; Engineering","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":[],"consensus_categories":[],"category_scores_codex":[0.00004122095,0.0001078698,0.00008393935,0.00005257107,0.00007259752,0.00006452246,0.0000384033,0.00004306992,0.00006311244],"category_scores_gemma":[0.000003388594,0.000108285,0.00003803238,0.00003139426,0.00001095335,0.0001191501,0.00001384297,0.00006590395,0.00001653537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009885358,"about_ca_system_score_gemma":0.000004167781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001618448,"about_ca_topic_score_gemma":8.89083e-8,"domain_scores_codex":[0.9995199,0.000003780015,0.0001128995,0.0001406952,0.00005742383,0.0001652364],"domain_scores_gemma":[0.9998053,0.00004945739,0.000007838028,0.00009810933,0.000004240066,0.00003509402],"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":[0.000002572787,0.000004517956,0.000003399592,0.0000940446,0.00002614813,0.000004797485,0.00006243285,0.9960593,0.002080318,0.001053075,0.000251738,0.0003576622],"study_design_scores_gemma":[0.0001030792,0.00001064382,0.00001112324,0.00003151854,0.00002475322,0.000006312295,0.000009812228,0.983832,0.008746614,0.001844045,0.005235277,0.0001448186],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003214577,0.0003231384,0.994619,0.00001224705,0.0002334861,0.0001722112,0.00005733043,0.000424642,0.0009433737],"genre_scores_gemma":[0.8166784,0.00004799026,0.1827882,0.0000194517,0.00006676369,0.00002446629,0.0001426193,0.00003989442,0.0001922549],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8134638,"threshold_uncertainty_score":0.4415735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02831944270515065,"score_gpt":0.265663065568575,"score_spread":0.2373436228634243,"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."}}