{"id":"W2167687810","doi":"10.1609/aiide.v1i1.18719","title":"Particle-Based Communication Among Game Agents","year":2005,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","topic":"Target Tracking and Data Fusion in Sensor Networks","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Particle filter; Inference; State space; State (computer science); Artificial intelligence; Space (punctuation); Distributed computing; Theoretical computer science; Algorithm; Mathematics; Kalman filter","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":[],"consensus_categories":[],"category_scores_codex":[0.0001744337,0.0001891626,0.0001755293,0.00006268451,0.0001359566,0.0006272083,0.001053793,0.0000507605,0.0000470257],"category_scores_gemma":[0.0001289212,0.0001399327,0.0000933989,0.000192845,0.0002407598,0.00132639,0.0004089234,0.0002353831,0.00004691195],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005957397,"about_ca_system_score_gemma":0.00001909327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001437996,"about_ca_topic_score_gemma":0.000005033608,"domain_scores_codex":[0.9985842,0.00001779631,0.0004377317,0.0003667702,0.0003431522,0.0002504243],"domain_scores_gemma":[0.998907,0.0001199211,0.000297728,0.0003169126,0.0002621168,0.0000963481],"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":[0.0002470026,0.001249414,0.00503808,0.0000276408,0.00005685724,7.971171e-7,0.004058106,0.0007679242,0.002510149,0.3246318,0.0006450259,0.6607673],"study_design_scores_gemma":[0.0001756827,0.0003820833,0.003141708,0.0007291629,0.0000172354,0.000004938229,0.001566724,0.6431706,0.3305692,0.01718036,0.002647512,0.0004147949],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.962148,0.00003427428,0.02371279,0.005252621,0.000212805,0.000409846,0.00001553492,0.00008882224,0.008125347],"genre_scores_gemma":[0.9987379,0.00003722547,0.0005203493,0.0004642803,0.00003095364,0.00002427209,0.000003259006,0.000008490279,0.0001732351],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6603525,"threshold_uncertainty_score":0.6048184,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04531111874754846,"score_gpt":0.2795922965332043,"score_spread":0.2342811777856558,"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."}}