{"id":"W4402474508","doi":"10.1109/ccece59415.2024.10667129","title":"Hierarchical Deep Reinforcement Learning with Cross-attention and Planning for Autonomous Roundabout Navigation","year":2024,"lang":"en","type":"article","venue":"","topic":"Robotic Path Planning Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Roundabout; Reinforcement learning; Computer science; Artificial intelligence; Motion planning; Human–computer interaction; Engineering; Transport engineering; Robot","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":[0.0003773436,0.0001281235,0.0001122839,0.00009864951,0.0002675208,0.00101852,0.0001756802,0.00005546596,0.000002748531],"category_scores_gemma":[0.0000316699,0.000101874,0.00003020512,0.0001835815,0.00005203371,0.0006579485,0.00008294467,0.0002033104,0.00001160841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006515827,"about_ca_system_score_gemma":0.00006520731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001285738,"about_ca_topic_score_gemma":2.856145e-7,"domain_scores_codex":[0.9988775,0.00002503945,0.0001985947,0.0004128785,0.0002168353,0.0002691109],"domain_scores_gemma":[0.9995018,0.0001617281,0.00004345152,0.0001504598,0.00006208817,0.00008047724],"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":[0.00003117177,0.00001769977,0.006911477,0.0002282097,0.00008175382,0.0001204668,0.00474246,0.8435575,0.0003706219,0.0622302,0.00009705735,0.08161138],"study_design_scores_gemma":[0.0002791645,0.0002574645,0.003964795,0.0001749711,0.00000877268,0.00009689987,0.00005087131,0.9933836,0.00008860441,0.0007936637,0.0007445489,0.0001565829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03195155,0.000158008,0.9658479,0.0002442322,0.0003132805,0.0002229837,2.564557e-7,0.000504136,0.0007576458],"genre_scores_gemma":[0.7041755,0.000001413713,0.2936983,0.000052131,0.00009927924,0.00004408029,0.00002629352,0.00001275565,0.001890226],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.672224,"threshold_uncertainty_score":0.9821607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01809749705778687,"score_gpt":0.2966906387817514,"score_spread":0.2785931417239645,"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."}}