{"id":"W4402474280","doi":"10.1109/ccece59415.2024.10667258","title":"Towards a Deep Reinforcement Learning Solution to the Coverage Path Planning Problem","year":2024,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"","keywords":"Reinforcement learning; Computer science; Motion planning; Path (computing); Artificial intelligence; Mathematical optimization; Mathematics; Computer network; Robot","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007434126,0.00015079,0.0001140554,0.0001104089,0.0002649426,0.0005920319,0.0006615417,0.00004580796,0.00001879955],"category_scores_gemma":[0.0000553257,0.00009988119,0.00005508953,0.000538618,0.00001282368,0.0003631823,0.000410339,0.0002946296,0.000398425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001189803,"about_ca_system_score_gemma":0.0001061761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009203154,"about_ca_topic_score_gemma":9.892011e-7,"domain_scores_codex":[0.9984456,0.00006936723,0.0002292947,0.0004040165,0.0004461964,0.0004054959],"domain_scores_gemma":[0.9993838,0.00009031638,0.0000352572,0.0003475881,0.00004031653,0.000102713],"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":[0.000001981919,0.00000559296,0.00005334359,0.00002140191,0.0000202673,0.00007766155,0.005655441,0.9018571,0.0001053127,0.01466868,0.005424513,0.07210872],"study_design_scores_gemma":[0.00006871654,0.0001403532,0.0002309858,0.0001359569,0.000005214241,0.00004133036,0.00007491877,0.9771328,0.0001109956,0.0004850192,0.02141807,0.0001556662],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001655108,0.0002602735,0.9733245,0.003262172,0.0006146313,0.0002747327,2.522116e-7,0.0007085081,0.02138943],"genre_scores_gemma":[0.6989118,0.000008467198,0.2950524,0.0009601862,0.0002109109,0.00007658549,0.000006275302,0.00001821869,0.004755108],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6987463,"threshold_uncertainty_score":0.5708977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02141267845718602,"score_gpt":0.2672183333223083,"score_spread":0.2458056548651223,"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."}}