{"id":"W4416013893","doi":"10.1609/aiide.v21i1.36831","title":"From Frustration to Fun: An Adaptive Problem-Solving Puzzle Game Powered by Genetic Algorithm","year":2025,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adaptive system; Genetic algorithm; Adaptive learning; Foundation (evidence); Game theory; Adaptive strategies; Work (physics)","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":[0.0005753461,0.0007643401,0.0003028279,0.0002931684,0.0003485954,0.0008396595,0.001125106,0.0007584124,0.002082945],"category_scores_gemma":[0.00331638,0.0001813738,0.0003645571,0.0001487118,0.0008087553,0.0009750945,0.001273464,0.0007547019,0.0003585523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000263399,"about_ca_system_score_gemma":0.0002750155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001086187,"about_ca_topic_score_gemma":0.001223786,"domain_scores_codex":[0.999622,0.0001653444,0.00001465217,0.00007069085,0.00008706276,0.00004023951],"domain_scores_gemma":[0.9992179,0.0005304333,0.00005665363,0.0000626229,0.00005321289,0.00007908428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003008072,0.003640469,0.02017908,0.000952108,0.0005288636,0.002040422,0.01117243,0.260224,0.1842256,0.06295595,0.01149219,0.4395808],"study_design_scores_gemma":[0.0004961716,0.001939966,0.008690085,0.00006843359,0.0001775889,0.0008387726,0.001070066,0.896848,0.02849496,0.03293447,0.02830764,0.0001339757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5992792,0.0001419609,0.3829338,0.0008608589,0.00008531033,0.0003269985,0.0001062083,0.001763284,0.0145023],"genre_scores_gemma":[0.8269251,0.0001226714,0.1670112,0.0002778571,0.0000158802,0.0002794518,0.0001550496,0.0001285361,0.005084266],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002082945,"threshold_uncertainty_score":0.006968141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02978024643061572,"score_gpt":0.2863465946732923,"score_spread":0.2565663482426765,"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."}}