{"id":"W2103700244","doi":"10.1109/isic.1996.556170","title":"A hybrid, self-organizing controller for multi-agent motion planning in a stationary environment","year":2002,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kingston Health Sciences Centre","funders":"","keywords":"Workspace; Controller (irrigation); Computer science; Control engineering; Decentralised system; Function (biology); Decentralization; Self-organization; Distributed computing; Multi-agent system; Control theory (sociology); Field (mathematics); Action (physics); Motion planning; Control (management); Artificial intelligence; Engineering; Robot; 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":[0.0002762779,0.0001327107,0.0001568538,0.0001329537,0.00009385282,0.00006210825,0.0002846063,0.00003434649,0.00002299257],"category_scores_gemma":[0.0000392572,0.0001285331,0.00003853838,0.00009551264,0.000009953577,0.0002973751,0.00008100741,0.00008779863,0.0001069732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001527993,"about_ca_system_score_gemma":0.000009097772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009113118,"about_ca_topic_score_gemma":1.41229e-7,"domain_scores_codex":[0.9987764,0.00005093821,0.0002719173,0.000380861,0.0002137955,0.0003061031],"domain_scores_gemma":[0.9994893,0.000137252,0.00007857965,0.0002045831,0.0000192132,0.00007106108],"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":[0.00003389695,0.002755681,0.02433992,0.0001122282,0.0002109847,0.0005457315,0.02779098,0.7874832,0.003617898,0.00606895,0.008577548,0.138463],"study_design_scores_gemma":[0.001647594,0.00005617178,0.007171347,0.0000167555,0.000003991882,0.00001939844,0.00005226271,0.9900848,0.0002161632,0.0001394502,0.0004384822,0.0001535849],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005225156,0.0001618446,0.9933136,0.0003638612,0.0001368225,0.0004546436,0.00000327679,0.0001934737,0.0001472916],"genre_scores_gemma":[0.2599285,0.00000636367,0.739331,0.0002437502,0.00002976919,0.00006687365,0.000004372356,0.00001060498,0.0003787323],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2547034,"threshold_uncertainty_score":0.5241429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05429070802103794,"score_gpt":0.2566456714373805,"score_spread":0.2023549634163426,"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."}}