{"id":"W409933044","doi":"10.1609/aiide.v8i1.12515","title":"Statechart-Based AI in Practice","year":2012,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Modular design; USable; Reuse; Computer science; Tree (set theory); Artificial intelligence; Software engineering; Point (geometry); Scale (ratio); Human–computer interaction; Programming language; Engineering; World Wide Web","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":[0.003658882,0.0006634264,0.0003692558,0.001042269,0.0007422713,0.004050668,0.00187099,0.001762423,0.0201842],"category_scores_gemma":[0.009783663,0.0007230568,0.0009133022,0.0008259108,0.003597168,0.005555217,0.002854219,0.00297105,0.00442129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001841175,"about_ca_system_score_gemma":0.002155622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004368934,"about_ca_topic_score_gemma":0.004251669,"domain_scores_codex":[0.9977245,0.0008877287,0.0001952935,0.0003396884,0.0006973859,0.0001554197],"domain_scores_gemma":[0.9959381,0.001994563,0.0001642896,0.001058445,0.0006590449,0.0001855801],"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":[0.0000360727,0.00004814506,0.0003632537,0.0003239378,0.0000292739,0.0001329722,0.0006770219,0.03406035,0.003045452,0.8884145,0.006719102,0.06614979],"study_design_scores_gemma":[0.00004140402,0.00005624757,0.0001243982,0.0002355902,0.00002983277,0.0001760794,0.0001659573,0.1413895,0.003632181,0.6680929,0.1860265,0.00002940753],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001950148,0.0004052906,0.9687203,0.001210378,0.0001201773,0.0000881104,0.0001012802,0.002546975,0.02485746],"genre_scores_gemma":[0.1644711,0.001557476,0.8156787,0.0005954661,0.0001042195,0.0004209942,0.0005343244,0.0007624914,0.01587532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0201842,"threshold_uncertainty_score":0.06752282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03933180337379474,"score_gpt":0.3042936714137457,"score_spread":0.264961868039951,"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."}}