{"id":"W4382866757","doi":"10.1609/icaps.v33i1.27218","title":"Symmetry Detection and Breaking in Linear Cost-Optimal Numeric Planning","year":2023,"lang":"en","type":"article","venue":"Proceedings of the International Conference on Automated Planning and Scheduling","topic":"AI-based Problem Solving and Planning","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Israel Academy of Sciences and Humanities","keywords":"Satisficing; Pruning; Symmetry (geometry); Symmetry breaking; Heuristic; Homogeneous space; Mathematics; Symmetry group; Rotational symmetry; Mathematical optimization; Computer science; Algorithm; Artificial intelligence; Physics; Geometry","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001841353,0.0004951882,0.0005772323,0.0009620874,0.0007004217,0.001228925,0.001090117,0.0006388963,0.002339829],"category_scores_gemma":[0.01202266,0.0004945481,0.0007204466,0.0008646065,0.001834242,0.001538526,0.00129843,0.001128915,0.0003038563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001284523,"about_ca_system_score_gemma":0.002028661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004145096,"about_ca_topic_score_gemma":0.002785133,"domain_scores_codex":[0.9979996,0.0006910728,0.0001181635,0.0002439449,0.000755051,0.0001921624],"domain_scores_gemma":[0.9936407,0.00400407,0.0007793259,0.0009701606,0.0004607676,0.0001449466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005214587,0.0001505075,0.004768291,0.0002854122,0.00005703154,0.000306835,0.0002558127,0.66646,0.01045907,0.1461484,0.001864578,0.1687227],"study_design_scores_gemma":[0.00002808394,0.00008426673,0.000492972,0.00002291902,0.0000120955,0.00007381625,0.00005576897,0.905581,0.006207759,0.08667267,0.0007561243,0.0000125101],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1885486,0.0002847545,0.80009,0.0003161123,0.00004081828,0.0001371574,0.0002392165,0.001212908,0.009130353],"genre_scores_gemma":[0.7546011,0.00009804885,0.2438144,0.00006053832,0.00001054154,0.00009025544,0.0002763148,0.0001164241,0.0009323491],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004145096,"threshold_uncertainty_score":0.009738088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03892980605732845,"score_gpt":0.2994059916473015,"score_spread":0.2604761855899731,"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."}}