{"id":"W3102089800","doi":"10.24963/ijcai.2021/294","title":"Deep Reinforcement Learning for Navigation in AAA Video Games","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ubisoft (Canada)","funders":"","keywords":"Reinforcement learning; Computer science; Variety (cybernetics); Video game; Representation (politics); Point (geometry); Artificial intelligence; Graph; Human–computer interaction; Multimedia; Theoretical computer science","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":[0.0007799813,0.0008413987,0.0007734823,0.0003440309,0.0002818658,0.0006971742,0.001028744,0.001006443,0.001949395],"category_scores_gemma":[0.003897334,0.0003610544,0.0003352245,0.0002565753,0.0008197419,0.001069911,0.0008345466,0.001614692,0.0003678276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001308339,"about_ca_system_score_gemma":0.001116156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01316022,"about_ca_topic_score_gemma":0.01154078,"domain_scores_codex":[0.9996693,0.0001310559,0.0000135821,0.00006298091,0.00005505954,0.0000680662],"domain_scores_gemma":[0.9990558,0.0006195145,0.00007959592,0.00004044433,0.0001327283,0.00007197396],"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":[0.0001109411,0.0001114353,0.001384689,0.00007456513,0.00003393039,0.00004296486,0.00005201163,0.9382269,0.0009549956,0.007211486,0.001751287,0.0500448],"study_design_scores_gemma":[0.000005663327,0.0000137225,0.00007300196,0.000003863642,0.00000187519,0.000002410093,0.000003968119,0.9962774,0.0001703229,0.003267934,0.0001778448,0.000001992559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1254405,0.001626806,0.8616315,0.00121366,0.0001749298,0.00008984138,0.0001786191,0.001916962,0.007727231],"genre_scores_gemma":[0.9476058,0.0002752887,0.04841177,0.0002248691,0.00003445492,0.00008101282,0.0001641556,0.00005494377,0.003147681],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01316022,"threshold_uncertainty_score":0.02616727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04080469939508952,"score_gpt":0.3152047365387844,"score_spread":0.2744000371436949,"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."}}