{"id":"W2982378153","doi":"10.1609/aiide.v15i1.5228","title":"Pathfinding and Abstraction with Dynamic Terrain Costs","year":2019,"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":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Pathfinding; Terrain; Abstraction; Computer science; Path (computing); Programming language; Theoretical computer science; Shortest path problem; Geography; Cartography","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":[0.0007378373,0.0008289021,0.0009028087,0.001132088,0.0008238362,0.001979138,0.001580588,0.0008199231,0.004978749],"category_scores_gemma":[0.007422019,0.0006227428,0.001037101,0.001306934,0.001562158,0.00582395,0.003733158,0.001913074,0.0003651773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183081,"about_ca_system_score_gemma":0.00113308,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006717709,"about_ca_topic_score_gemma":0.008857869,"domain_scores_codex":[0.9990121,0.0002847196,0.00005411596,0.0001679463,0.0003345016,0.0001465746],"domain_scores_gemma":[0.9969374,0.001609776,0.0003032284,0.0007215971,0.0002736806,0.0001543645],"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":[0.0002810254,0.00007504997,0.0024844,0.0002927796,0.0001025284,0.0003202234,0.0008974342,0.4560907,0.004667693,0.4152906,0.00210938,0.1173883],"study_design_scores_gemma":[0.00006950976,0.0001372975,0.00211941,0.00008379074,0.00009762275,0.0004838443,0.0004196935,0.6316539,0.003080441,0.3469685,0.01481963,0.00006624297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05949019,0.0004098665,0.9293571,0.0003914877,0.00003933689,0.00006873802,0.0001122953,0.0002864942,0.009844502],"genre_scores_gemma":[0.5896496,0.0006770304,0.4036146,0.00005767356,0.00003534425,0.0001347959,0.0002505359,0.0001452829,0.005435205],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006717709,"threshold_uncertainty_score":0.01665556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02032147801674987,"score_gpt":0.266035848648368,"score_spread":0.2457143706316181,"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."}}