{"id":"W1562987626","doi":"10.1023/a:1025697810124","title":"A Formal Approach to Agent Design: An Overview of Constraint-Based Agents","year":2003,"lang":"en","type":"article","venue":"Constraints","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Constraint (computer-aided design); Computer science; Automaton; Formal verification; Formal specification; Constraint logic programming; Constraint satisfaction problem; Theoretical computer science; Constraint graph; Constraint satisfaction; Programming language; Artificial intelligence; Mathematics","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":[0.0009585633,0.0002371485,0.0003297555,0.0001393865,0.0001171026,0.00009134257,0.0008527603,0.00009991667,0.0001567926],"category_scores_gemma":[0.0001972438,0.0002137711,0.0001296218,0.000423507,0.0003005032,0.0003340657,0.00009775264,0.0001205143,0.0000851223],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005263215,"about_ca_system_score_gemma":0.0004573817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004493083,"about_ca_topic_score_gemma":0.000001343257,"domain_scores_codex":[0.9979647,0.0002886153,0.0003731098,0.0005087238,0.0003123678,0.0005524715],"domain_scores_gemma":[0.9985595,0.00009185824,0.0001355498,0.0006739355,0.0001511669,0.0003879358],"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":[0.00001644037,0.001030453,0.0008517861,0.0001447605,0.00006298232,0.00005064995,0.002461118,0.0006740429,0.0010379,0.8408592,0.0009706905,0.15184],"study_design_scores_gemma":[0.03253066,0.008999288,0.03981673,0.002073249,0.0005130437,0.003297749,0.005259311,0.5770463,0.187175,0.06036734,0.07162672,0.01129453],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005656959,0.0002259605,0.9158605,0.00002684829,0.0002774059,0.0005018538,0.000008767128,0.000103326,0.07733841],"genre_scores_gemma":[0.8259267,0.000006407081,0.1734606,0.0004779109,0.00001722221,0.00003056114,0.000003974127,0.000009968703,0.00006658106],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8202698,"threshold_uncertainty_score":0.8717332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1476368975762101,"score_gpt":0.3154502977111036,"score_spread":0.1678134001348935,"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."}}