{"id":"W2023332909","doi":"10.1007/s12652-015-0265-z","title":"Decision making under subjective uncertainty in argumentation-based agent negotiation","year":2015,"lang":"en","type":"article","venue":"Journal of Ambient Intelligence and Humanized Computing","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Argumentation theory; Computational intelligence; Negotiation; Computer science; Artificial intelligence; Group decision-making; Management science; Multi-agent system; Psychology; Epistemology; Sociology","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":[0.01930951,0.0007196324,0.001894987,0.001491658,0.002052001,0.007203801,0.002190465,0.003379687,0.003213592],"category_scores_gemma":[0.08346663,0.0009673071,0.001153371,0.001502274,0.00377278,0.008576269,0.00398507,0.003218486,0.0002819142],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002072033,"about_ca_system_score_gemma":0.00195309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002166241,"about_ca_topic_score_gemma":0.001145491,"domain_scores_codex":[0.98574,0.01015431,0.0007411063,0.0007463343,0.001930389,0.0006877187],"domain_scores_gemma":[0.9283997,0.06257438,0.002855338,0.001467219,0.00333723,0.00136598],"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":[0.0008280283,0.0002513184,0.002460377,0.0003299268,0.000297908,0.0007599531,0.003469941,0.2723179,0.001425722,0.6900037,0.0009520056,0.02690331],"study_design_scores_gemma":[0.00008292868,0.00007901957,0.000327905,0.00003224183,0.00005891605,0.00005189268,0.0002870295,0.6166742,0.0003233607,0.3815531,0.0004920269,0.00003734689],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2389505,0.0008094221,0.7381225,0.002467807,0.0001632472,0.000171862,0.00007115595,0.00007813684,0.01916538],"genre_scores_gemma":[0.9705812,0.0001606033,0.02774277,0.00006341207,0.00006061549,0.00007559584,0.00003655276,0.00001594206,0.001263337],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01930951,"threshold_uncertainty_score":0.1021196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0673872195205561,"score_gpt":0.3303929930902882,"score_spread":0.2630057735697321,"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."}}