{"id":"W2065794244","doi":"10.11120/ital.2005.04030005","title":"Teaching Multi-Agent Systems using the ARES Simulator","year":2005,"lang":"en","type":"article","venue":"Innovation in Teaching and Learning in Information and Computer Sciences","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Testbed; Computer science; Perspective (graphical); Simulation; Software engineering; Human–computer interaction; Systems engineering; Engineering; World Wide Web; Artificial intelligence","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":[0.005428436,0.0001202071,0.0001301525,0.000626098,0.0009637954,0.0009714136,0.0002902274,0.00005334163,5.984938e-7],"category_scores_gemma":[0.0001553394,0.00008885096,0.00001248669,0.0005609913,0.00005827646,0.002815619,0.0001419114,0.0006013432,0.000002596877],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005794993,"about_ca_system_score_gemma":0.00004024757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008751294,"about_ca_topic_score_gemma":0.00001934103,"domain_scores_codex":[0.9981763,0.0004694417,0.0006700251,0.0002035368,0.0002828659,0.0001978335],"domain_scores_gemma":[0.9992599,0.0002154503,0.0003312103,0.0001161063,0.00005205803,0.0000253134],"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":[0.000001582912,0.00002421719,0.02888151,0.00003625567,0.000003250385,3.790199e-7,0.03329603,0.6105326,0.00003968408,0.06760547,0.00002815875,0.2595508],"study_design_scores_gemma":[0.0003182134,0.0000291069,0.02013051,0.0001074065,6.946044e-7,0.00001417159,0.001082266,0.9693877,0.000003722816,0.0000214594,0.008787226,0.0001175434],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4734356,0.00006460981,0.5254536,0.0005409245,0.0002282819,0.0001233012,1.531638e-7,0.0000529452,0.0001005911],"genre_scores_gemma":[0.9592619,0.000005400123,0.04009252,0.0005095391,0.00008532657,0.000007478801,0.000001834908,0.000002388151,0.00003360996],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4858263,"threshold_uncertainty_score":0.9367364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03744731267998497,"score_gpt":0.2969011585935654,"score_spread":0.2594538459135804,"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."}}