{"id":"W2501623012","doi":"10.1007/978-3-642-28499-1","title":"Adaptive and Learning Agents","year":2012,"lang":"en","type":"book","venue":"Lecture notes in computer science","topic":"Multi-Agent Systems and Negotiation","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Adaptive learning; Volume (thermodynamics); Artificial intelligence; Operations research; Engineering","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":[0.0003486336,0.0006237687,0.0004476166,0.0005130099,0.0005626769,0.002222474,0.0006992065,0.001116556,0.01277163],"category_scores_gemma":[0.001211559,0.0002883292,0.0002609949,0.0007188685,0.001577596,0.003072719,0.001149287,0.001565262,0.002992013],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008516038,"about_ca_system_score_gemma":0.0004555077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006250738,"about_ca_topic_score_gemma":0.0006771719,"domain_scores_codex":[0.999761,0.00005781544,0.00001064387,0.00004861129,0.0001040044,0.00001793615],"domain_scores_gemma":[0.999757,0.0001089596,0.00001463657,0.00005791752,0.00004074509,0.00002071644],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001527909,0.00003085636,0.00009389973,0.0001239523,0.00001201645,0.00004798125,0.0002850838,0.004637537,0.0006226311,0.8444859,0.02430143,0.1253433],"study_design_scores_gemma":[0.000008309061,0.00002186892,0.00017075,0.00006813517,0.000009068182,0.0001113542,0.00009405461,0.008656053,0.0006870569,0.7213193,0.2688444,0.000009784091],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.007429772,0.03824573,0.2465526,0.005889683,0.002359779,0.00009900823,0.000130896,0.0005854053,0.6987072],"genre_scores_gemma":[0.1777362,0.01858856,0.06002229,0.001165634,0.001219788,0.0002351821,0.00028091,0.0002349514,0.7405164],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.01277163,"threshold_uncertainty_score":0.04272538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0275544932149063,"score_gpt":0.2545634117968054,"score_spread":0.2270089185818991,"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."}}