{"id":"W4405974740","doi":"10.1109/pimrc59610.2024.10817259","title":"Hierarchical Deep Reinforcement Learning with Information Freshness in Smart Agriculture Applications","year":2024,"lang":"en","type":"article","venue":"","topic":"Smart Agriculture and AI","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Reinforcement learning; Computer science; Agriculture; Artificial intelligence; Geography","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":[0.0008265253,0.0008016595,0.0008077044,0.0002300068,0.0002722436,0.0005990195,0.001051551,0.0007921318,0.001588746],"category_scores_gemma":[0.002001574,0.0003423863,0.0003066489,0.0002633548,0.0005657864,0.0008635165,0.0007986618,0.001269685,0.0002104879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008839142,"about_ca_system_score_gemma":0.001056231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008685858,"about_ca_topic_score_gemma":0.009039087,"domain_scores_codex":[0.9997517,0.00006348919,0.00001221272,0.00006245519,0.0000431488,0.00006699672],"domain_scores_gemma":[0.9992033,0.0004789362,0.00008473093,0.00003757364,0.0001316031,0.00006391844],"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":[0.00008369386,0.00008679659,0.0008769307,0.00004903975,0.00003106402,0.00005560399,0.00004225439,0.9570455,0.00144098,0.002583064,0.001078988,0.03662619],"study_design_scores_gemma":[0.000004849783,0.00001816271,0.00005715359,0.000001969411,0.000003239961,0.000003008643,0.000003033846,0.99873,0.0001398387,0.0009488806,0.00008809246,0.00000173105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1136923,0.001361337,0.8789877,0.0006727997,0.0001140817,0.00006276475,0.000110613,0.001016162,0.003982319],"genre_scores_gemma":[0.9691653,0.0001610354,0.02852585,0.0001661748,0.00002948661,0.00004422721,0.00007712575,0.0000396559,0.001791199],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008685858,"threshold_uncertainty_score":0.01727062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005563082619604932,"score_gpt":0.189598100403462,"score_spread":0.1840350177838571,"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."}}