{"id":"W2918311828","doi":"10.1109/tvt.2019.2902318","title":"A Game Theory Based Efficient Computation Offloading in an UAV Network","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":176,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Computation offloading; Computer science; Distributed computing; Computation; Mobile device; Server; Edge computing; Mobile edge computing; Energy consumption; Enhanced Data Rates for GSM Evolution; Nash equilibrium; Game theory; Mathematical optimization; Computer network; Artificial intelligence; Operating system; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000634692,0.0008972061,0.0008559292,0.0004885498,0.0007020208,0.001238797,0.001204333,0.0009462368,0.002586103],"category_scores_gemma":[0.00143723,0.0003377177,0.0006209647,0.0004655036,0.000919282,0.001072452,0.001135657,0.0007206615,0.0002467226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001545477,"about_ca_system_score_gemma":0.001531836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01103302,"about_ca_topic_score_gemma":0.008079903,"domain_scores_codex":[0.9994148,0.0002228974,0.00002051772,0.0001078251,0.00009913818,0.0001349155],"domain_scores_gemma":[0.9993604,0.0004049967,0.00005472826,0.00002705584,0.00008464378,0.00006831976],"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":[0.00007561447,0.00003965554,0.0003727487,0.00004721713,0.00001885528,0.0001956459,0.00006135178,0.9695722,0.001819683,0.01923131,0.0008825667,0.007683044],"study_design_scores_gemma":[0.000007651936,0.00001651893,0.0000451732,0.000002927576,0.000003421447,0.00001815931,0.00001569266,0.9965197,0.0001705111,0.002931495,0.0002661359,0.000002615685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06945182,0.0002882068,0.9194855,0.0003865198,0.00007822556,0.0002051192,0.0001179607,0.0001607345,0.009825954],"genre_scores_gemma":[0.9137502,0.0002841402,0.07978631,0.0001257004,0.00002800375,0.0001993451,0.0001013555,0.00003817266,0.005686805],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01103302,"threshold_uncertainty_score":0.02193761,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004389531914222688,"score_gpt":0.2014098216846928,"score_spread":0.1970202897704701,"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."}}