{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001921859,0.0000609615,0.00007093622,0.00005724416,0.0001667709,0.0003908539,0.0008858822,0.00003522148,0.00002027139],"category_scores_gemma":[0.0001036561,0.0000565206,0.00001994828,0.00006723006,0.00004421549,0.002156234,0.0002449341,0.00006192695,0.0001793893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002861017,"about_ca_system_score_gemma":0.00003252181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006028673,"about_ca_topic_score_gemma":0.0004654287,"domain_scores_codex":[0.9993394,0.00002300674,0.0001548553,0.0002041702,0.0001183238,0.0001602293],"domain_scores_gemma":[0.99911,0.00002440854,0.00007769228,0.000719906,0.00003677095,0.00003123994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009582024,0.0001122788,0.09161707,0.00001100892,0.000006758941,0.00006964389,0.005149547,0.004197712,0.006408553,0.4751469,0.001514504,0.4157564],"study_design_scores_gemma":[0.0000735531,0.00003037223,0.009873455,0.00003820383,0.00000134295,0.000004610947,0.000217405,0.7733045,0.05395789,0.160472,0.001766526,0.0002600817],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.108688,0.00001651631,0.878298,0.000986896,0.0004963315,0.00008669574,1.908952e-7,0.00006628953,0.01136108],"genre_scores_gemma":[0.9349951,0.000005564878,0.06449916,0.0001110701,0.0000540913,0.000003322938,2.131219e-7,0.000003223548,0.0003282411],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8263071,"threshold_uncertainty_score":0.3769013,"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."}}