{"id":"W4402426965","doi":"10.48550/arxiv.2408.06553","title":"Centralization vs. decentralization in multi-robot sweep coverage with ground robots and UAVs","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Office of Naval Research Global; Office of Naval Research; China Scholarship Council; European Commission; Government of Ontario; University of Ottawa","keywords":"Decentralization; Robot; Business; Computer science; Artificial intelligence; Economics; Market economy","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001968332,0.0004103962,0.000831691,0.0005195368,0.0004081975,0.0005405505,0.0005723856,0.0005739675,0.0004453793],"category_scores_gemma":[0.004512397,0.0002733636,0.000341811,0.0005163628,0.001032488,0.00131869,0.001106013,0.0005639053,0.00007616296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005781628,"about_ca_system_score_gemma":0.0006101717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002305832,"about_ca_topic_score_gemma":0.001809513,"domain_scores_codex":[0.999167,0.0003718587,0.00002809445,0.0001461098,0.0001513008,0.0001356884],"domain_scores_gemma":[0.9962529,0.002221899,0.00067163,0.0003751401,0.000252469,0.0002259113],"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":[0.0001973082,0.00006288662,0.001586338,0.00004490379,0.000024286,0.00003437827,0.00005857905,0.9764792,0.002455197,0.003387765,0.0001746572,0.0154944],"study_design_scores_gemma":[0.00004551524,0.0002381274,0.00175163,0.000006646252,0.00001343981,0.00003427924,0.00007269694,0.9910188,0.002263081,0.004277996,0.0002691348,0.000008676907],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5385286,0.0007954196,0.4569803,0.0003148579,0.00002080343,0.00008962802,0.00005148966,0.0003736332,0.00284529],"genre_scores_gemma":[0.981995,0.00009716137,0.01738223,0.00001927688,0.00001271795,0.00003414564,0.00002674776,0.00001771628,0.0004149026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002305832,"threshold_uncertainty_score":0.01040971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07412246750598184,"score_gpt":0.2076468936296617,"score_spread":0.1335244261236799,"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."}}