{"id":"W3212900133","doi":"10.1109/tcns.2022.3153872","title":"Scalable Operator Allocation for Multirobot Assistance: A Restless Bandit Approach","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Control of Network Systems","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de la Défense Nationale","keywords":"Scalability; Leverage (statistics); Robot; Computer science; Operator (biology); Mathematical optimization; Heuristic; Robot kinematics; Distributed computing; Artificial intelligence; Mobile robot; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004530754,0.0002350632,0.0007202901,0.0003406066,0.001056481,0.0001821582,0.0009268795,0.0001024631,0.0001356004],"category_scores_gemma":[0.0001113912,0.0002013753,0.0002784844,0.00140153,0.0001234909,0.0002947421,0.000005547161,0.0004159614,0.000021664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003042918,"about_ca_system_score_gemma":0.0002187867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005449543,"about_ca_topic_score_gemma":0.00003159976,"domain_scores_codex":[0.9944759,0.0008660421,0.001128275,0.000757884,0.002199382,0.0005724975],"domain_scores_gemma":[0.9951455,0.002677402,0.0004285468,0.0008692804,0.0007145382,0.0001647124],"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":[0.0008014103,0.0002802065,0.00003522494,0.0000264903,0.00008899849,0.000002014076,0.00009778426,0.9881586,0.0004523965,0.0001414942,0.00436528,0.005550031],"study_design_scores_gemma":[0.003539214,0.0004683207,0.00007844526,0.00002980423,0.00004065413,0.00001425182,0.0008746971,0.9750979,0.0002188924,0.0002098444,0.01919007,0.000237938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0009635644,0.000691595,0.9927296,0.0002052945,0.002435328,0.002265326,0.0004255701,0.00006006501,0.0002236763],"genre_scores_gemma":[0.9891362,0.00001215012,0.002691304,0.00006101017,0.0003539973,0.002889061,0.00001060845,0.00004330076,0.004802421],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9900383,"threshold_uncertainty_score":0.8211846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08808758998774956,"score_gpt":0.3626182202265537,"score_spread":0.2745306302388041,"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."}}