{"id":"W1537414353","doi":"10.1007/978-3-642-04128-0_23","title":"Optimality and Competitiveness of Exploring Polygons by Mobile Robots","year":2009,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec en Outaouais","funders":"","keywords":"Polygon (computer graphics); Simple polygon; Mobile robot; Focus (optics); Computer science; Robot; Trajectory; Boundary (topology); Metric (unit); Point (geometry); Square (algebra); Convex polygon; Point in polygon; Motion planning; Computer vision; Artificial intelligence; Regular polygon; Mathematics; Computer graphics (images); Geometry; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001016489,0.0009265455,0.002194457,0.001109518,0.001021165,0.003239212,0.002236324,0.001677635,0.008525225],"category_scores_gemma":[0.007166595,0.000834673,0.001508514,0.001796576,0.003246684,0.003742098,0.002461837,0.002257241,0.0008896523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001366246,"about_ca_system_score_gemma":0.001339726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003892382,"about_ca_topic_score_gemma":0.003120011,"domain_scores_codex":[0.9987298,0.0003380318,0.00005335719,0.0002214293,0.0003246309,0.0003327664],"domain_scores_gemma":[0.995675,0.002938425,0.000325287,0.0003103496,0.0002601549,0.000490679],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009633589,0.0001611635,0.002825569,0.0003934371,0.00007495656,0.0002629142,0.0005356424,0.3093517,0.007682095,0.6156241,0.007191185,0.0549338],"study_design_scores_gemma":[0.0001470483,0.0002501175,0.002198627,0.00006966119,0.00005226615,0.0003014136,0.0003542723,0.3425156,0.003435353,0.6435816,0.007050765,0.00004329174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5671185,0.002916074,0.2971343,0.001729951,0.0002212913,0.0001635011,0.0008156534,0.0004800522,0.1294207],"genre_scores_gemma":[0.8861283,0.001445412,0.0923435,0.0001232047,0.0002040624,0.0002132875,0.0007557265,0.0005391051,0.01824735],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.008525225,"threshold_uncertainty_score":0.02851969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03201215920856491,"score_gpt":0.2640694325269873,"score_spread":0.2320572733184224,"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."}}