{"id":"W2101355691","doi":"10.1109/icinfa.2011.5949001","title":"Fuzzy logic-based multi-robot cooperation for object-pushing","year":2011,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Robot; Fuzzy logic; Object (grammar); Computer science; Artificial intelligence; Scheme (mathematics); Robotics; Control engineering; Fuzzy control system; Mobile robot; Engineering; Mathematics","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":[0.0003627409,0.0001363669,0.0001436181,0.00008374675,0.0001637285,0.000111758,0.0006057518,0.00007461147,0.0000131595],"category_scores_gemma":[0.0002110194,0.000114632,0.00005506939,0.0001961217,0.00002421784,0.0003939314,0.00006849516,0.00008221149,0.0000923064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002859706,"about_ca_system_score_gemma":0.0001141339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009499221,"about_ca_topic_score_gemma":0.000007895855,"domain_scores_codex":[0.9989252,0.00004519555,0.0002128162,0.000379701,0.0001378452,0.0002992198],"domain_scores_gemma":[0.9991482,0.000107487,0.00006928863,0.0004203351,0.0001429771,0.0001117166],"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":[0.0001423496,0.002135079,0.005968401,0.0002071893,0.0001987039,0.0001708705,0.01449359,0.2779462,0.02565137,0.5574214,0.01755958,0.09810521],"study_design_scores_gemma":[0.0007888992,0.0001657705,0.002683878,0.00001371319,0.000005565327,0.000004665235,0.00002376392,0.9889128,0.006184711,0.0008766252,0.0001142771,0.0002252913],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002319047,0.00003034825,0.994469,0.0003146825,0.0005281903,0.0003105273,0.000001699652,0.0004167926,0.003696839],"genre_scores_gemma":[0.1243778,4.32359e-7,0.8738993,0.00127452,0.00004213915,0.00004440645,0.000006319329,0.000009089061,0.0003459656],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7109666,"threshold_uncertainty_score":0.4674558,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.128980773262666,"score_gpt":0.294442243403227,"score_spread":0.165461470140561,"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."}}