{"id":"W4401024943","doi":"10.24963/ijcai.2024/964","title":"DGL: Dynamic Global-Local Information Aggregation for Scalable VRP Generalization with Self-Improvement Learning","year":2024,"lang":"en","type":"article","venue":"","topic":"Reinforcement Learning in Robotics","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Research (Canada)","funders":"Grantová Agentura České Republiky; Ministerstvo Školství, Mládeže a Tělovýchovy","keywords":"Computer science; Imperfect; Perfect information; Algorithm; Mathematics; Mathematical economics","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":[0.0002866539,0.0001520116,0.0001017337,0.0001115877,0.0001824314,0.0008127431,0.0002712359,0.00006671597,0.00001291112],"category_scores_gemma":[0.00002485919,0.0001254922,0.00004121668,0.0005827565,0.00001936064,0.00236516,0.00009146895,0.00009794771,0.0000883051],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004118238,"about_ca_system_score_gemma":0.0001363736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003106654,"about_ca_topic_score_gemma":0.00001046679,"domain_scores_codex":[0.9987732,0.00002386947,0.0003008994,0.0002431927,0.0003828391,0.0002759792],"domain_scores_gemma":[0.9993976,0.00003933919,0.0001018146,0.00022551,0.0001765105,0.00005916683],"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":[0.000004464602,0.000006276439,0.0001421806,0.0001139634,0.00002879748,5.760306e-7,0.0002527858,0.8698249,0.00003650431,0.06063905,0.0003448666,0.06860563],"study_design_scores_gemma":[0.0003034257,0.0003690028,0.0001016207,0.00006073247,0.00001705883,0.000006765534,0.00005875653,0.980464,0.0004667242,0.0003660792,0.01760945,0.000176424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001439078,0.00003193457,0.9934969,0.0004446213,0.0003555013,0.000506789,0.000001050804,0.001079788,0.002644326],"genre_scores_gemma":[0.7535954,0.00003000774,0.243904,0.0003631974,0.00004107634,0.00008620473,0.000138302,0.00001540373,0.001826384],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7521563,"threshold_uncertainty_score":0.78373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004381780029235462,"score_gpt":0.226708728087707,"score_spread":0.2223269480584715,"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."}}