{"id":"W3037624633","doi":"10.1609/aaai.v34i09.7124","title":"Abstraction and Refinement in Games with Dynamic Weighted Terrain","year":2020,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Artificial Intelligence in Games","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Pathfinding; Abstraction; Terrain; Computer science; Programming language; Work (physics); Theoretical computer science; Geography; Epistemology; Engineering; 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":[0.001612158,0.0008261151,0.0008691289,0.0009890114,0.001434804,0.002432204,0.001835842,0.001384449,0.006126009],"category_scores_gemma":[0.008796122,0.0007597111,0.001561413,0.001057082,0.005069362,0.007594896,0.005875109,0.002527541,0.0004218862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001663605,"about_ca_system_score_gemma":0.001115341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01418094,"about_ca_topic_score_gemma":0.01361631,"domain_scores_codex":[0.9982384,0.000706749,0.0001267801,0.0002806991,0.0003648101,0.0002825081],"domain_scores_gemma":[0.9973591,0.001582531,0.000171553,0.0004369268,0.0001795034,0.0002703068],"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":[0.0000769973,0.00002147846,0.0004316522,0.00005590162,0.00002216658,0.0001175518,0.001153607,0.05535916,0.0009255424,0.9303589,0.000595928,0.01088111],"study_design_scores_gemma":[0.00004134181,0.00003447672,0.0001829548,0.00002052825,0.00001816472,0.00005110688,0.0003680653,0.1500483,0.0005106958,0.8436989,0.005006555,0.00001890811],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08727931,0.000219064,0.886058,0.0007390099,0.00005969317,0.0001094335,0.00009910042,0.0002989416,0.02513743],"genre_scores_gemma":[0.7791355,0.000282106,0.2072015,0.0001143489,0.00003250191,0.000160351,0.0002087966,0.0001195313,0.01274523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01418094,"threshold_uncertainty_score":0.02819675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05116744541704771,"score_gpt":0.2847045815880936,"score_spread":0.2335371361710459,"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."}}