{"id":"W1659382545","doi":"10.1609/socs.v2i1.18205","title":"A Polynomial-Time Algorithm for Non-Optimal Multi-Agent Pathfinding","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":64,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Pathfinding; Tree (set theory); Computer science; Time complexity; Variety (cybernetics); Constructive; Algorithm; Mathematical optimization; Theoretical computer science; Mathematics; Artificial intelligence; Shortest path problem; Process (computing); Combinatorics; Graph; Programming language","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":[0.0008462198,0.000222402,0.0002805255,0.0001191813,0.0002522071,0.0003614081,0.002512117,0.000121144,0.00001052205],"category_scores_gemma":[0.0002780436,0.0001925385,0.0002451869,0.0004116342,0.00006843813,0.0003564325,0.001054053,0.0003059406,0.00003512385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003243881,"about_ca_system_score_gemma":0.0002068561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002770525,"about_ca_topic_score_gemma":8.403142e-8,"domain_scores_codex":[0.9973431,0.00002030146,0.0004227614,0.0006087325,0.001169475,0.0004356575],"domain_scores_gemma":[0.9979525,0.0002604668,0.0002290147,0.0002517318,0.001178977,0.0001273113],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002567453,0.002839665,0.002353979,0.0001567265,0.0007453046,0.00004066743,0.003801944,0.002613235,0.8907481,0.03795072,0.02989229,0.02860058],"study_design_scores_gemma":[0.00220968,0.0002412621,0.0004757571,0.000165239,0.00001510094,0.00003594224,0.00005090627,0.5922694,0.4019206,0.0003560354,0.002003349,0.0002566628],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.4941734,0.0001123506,0.3657448,0.03994996,0.0767971,0.004864091,0.0003642068,0.0008049646,0.01718916],"genre_scores_gemma":[0.4485005,0.00001990117,0.5432491,0.0004510542,0.002280093,0.0002197212,0.0000235041,0.00009002596,0.005166026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5896562,"threshold_uncertainty_score":0.7851494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01992492518198036,"score_gpt":0.2729742948879271,"score_spread":0.2530493697059467,"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."}}