{"id":"W4382204418","doi":"10.1109/phm58589.2023.00046","title":"An efficient algorithm for task allocation with multi-agent collaboration constraints","year":2023,"lang":"en","type":"article","venue":"","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Task (project management); Mathematical optimization; Constraint (computer-aided design); Nash equilibrium; Function (biology); Greedy algorithm; Game theory; Algorithm; Task analysis; 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":[0.001751225,0.00008733715,0.0001101773,0.0001515177,0.0002478682,0.0001906957,0.0002895118,0.00004037995,0.0001703914],"category_scores_gemma":[0.0002063368,0.00005870935,0.00002815584,0.001312105,0.0001440849,0.0001362826,0.00001873345,0.00003274728,0.0007403492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002300608,"about_ca_system_score_gemma":0.0000940493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003887549,"about_ca_topic_score_gemma":0.00003761725,"domain_scores_codex":[0.9986184,0.00008396254,0.0002866806,0.0003830931,0.0004579153,0.0001699618],"domain_scores_gemma":[0.9983782,0.0004360332,0.0001064115,0.0004188701,0.0005583469,0.0001021904],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004905326,0.0005514518,0.0002240184,0.000004179426,0.00002647487,0.000002219176,0.003466462,0.07091331,0.01907129,0.08342393,0.005939,0.8163286],"study_design_scores_gemma":[0.0007770902,0.0001610865,0.002156172,0.000004321585,0.00001186415,0.000002706183,0.01094398,0.9682277,0.005584633,0.004712212,0.007259411,0.000158754],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1214217,0.000002314252,0.8761607,0.0008192378,0.00008971932,0.0007012927,0.00009256921,0.0001507399,0.0005616817],"genre_scores_gemma":[0.9425735,9.636248e-7,0.05468559,0.0001488668,0.00003735421,0.0002507531,0.00008921798,0.00000863925,0.002205086],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8973144,"threshold_uncertainty_score":0.9515939,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09092074280888283,"score_gpt":0.411757806660983,"score_spread":0.3208370638521001,"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."}}