{"id":"W4404445012","doi":"10.1609/aiide.v20i1.31877","title":"Procedural Content Generation in Games: A Survey with Insights on Emerging LLM Integration","year":2024,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Natural Language Processing Techniques","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Content (measure theory); Computer science; Psychology; Mathematics","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":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002140918,0.0002493476,0.0002075239,0.000267249,0.00007099369,0.001084644,0.0005266539,0.00005419143,0.000005520662],"category_scores_gemma":[0.000240517,0.0001491709,0.00005475249,0.0004505524,0.0001134646,0.001746263,0.0001701335,0.0003396398,0.000007696887],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001541604,"about_ca_system_score_gemma":0.00005406513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006525669,"about_ca_topic_score_gemma":0.00007603697,"domain_scores_codex":[0.998437,0.00002061993,0.0004123504,0.0005409524,0.000378469,0.0002105796],"domain_scores_gemma":[0.9991924,0.00009233987,0.000173214,0.0001339752,0.000357583,0.00005044892],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004274138,0.0004828727,0.000339777,0.00008838636,0.0000458678,0.000006641999,0.01109632,0.00002431664,0.04389359,0.536793,0.0001257928,0.4066761],"study_design_scores_gemma":[0.00005716518,0.001399426,0.000261327,0.002648308,0.000007356219,0.00001368104,0.002261263,0.1508344,0.813429,0.02871756,0.00004932704,0.0003211921],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9350517,0.000200203,0.058625,0.002801861,0.0003080073,0.0008538119,0.00001231823,0.000155671,0.001991461],"genre_scores_gemma":[0.9987599,0.00003201565,0.0007268225,0.0002459816,0.00002990694,0.00006514038,0.000006405675,0.00001207057,0.0001217919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7695354,"threshold_uncertainty_score":0.9999523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07120850862497619,"score_gpt":0.3041764801660764,"score_spread":0.2329679715411002,"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."}}