{"id":"W2753254616","doi":"10.1145/3102071.3106345","title":"Exploration in NetHack using occupancy maps","year":2017,"lang":"en","type":"article","venue":"","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Computer science; Occupancy; Automation; Face (sociological concept); Artificial intelligence; Point (geometry); Robotics; Resource (disambiguation); Machine learning; Feature (linguistics); Heuristic; Robot; Human–computer interaction; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004856437,0.0006521294,0.0007077337,0.0004555814,0.0005961228,0.001015902,0.0009736277,0.0005047657,0.002445221],"category_scores_gemma":[0.00176488,0.0004709135,0.0004248741,0.00037617,0.0008748048,0.001564069,0.002319056,0.0004902084,0.0002960889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004820907,"about_ca_system_score_gemma":0.000555665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00485205,"about_ca_topic_score_gemma":0.006068668,"domain_scores_codex":[0.9995634,0.0001531473,0.00001811817,0.00006840289,0.0001144662,0.00008244419],"domain_scores_gemma":[0.9991224,0.0005561843,0.00005806824,0.00008396459,0.00006155255,0.0001176621],"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":[0.0003958967,0.0000917529,0.001719054,0.0001054284,0.00005173258,0.0002463828,0.0003316202,0.9255567,0.00899218,0.01580156,0.000703001,0.04600479],"study_design_scores_gemma":[0.00001452169,0.00005547814,0.0002667495,0.00000578476,0.000006802677,0.00005367774,0.00005922661,0.9896606,0.001669792,0.007301351,0.0008945281,0.00001141911],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2014775,0.0003356039,0.789135,0.0001219344,0.00003761527,0.00009677639,0.0001128651,0.00125454,0.007428207],"genre_scores_gemma":[0.899184,0.0001162717,0.09791679,0.00003005593,0.000005944957,0.00009252018,0.0000870997,0.00009354884,0.002473907],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00485205,"threshold_uncertainty_score":0.009647608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1950536570043825,"score_gpt":0.3803645111026333,"score_spread":0.1853108540982507,"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."}}