{"id":"W4285604285","doi":"10.24963/ijcai.2022/360","title":"Epistemic Logic of Likelihood and Belief","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence","topic":"Logic, Reasoning, and Knowledge","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Probabilistic logic; Computer science; Sublanguage; Probabilistic argumentation; Semantics (computer science); Belief revision; Modal logic; Theoretical computer science; Event (particle physics); Artificial intelligence; Epistemic modal logic; Datalog; Epistemology; Multimodal logic; Description logic; Programming language; Modal","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":[0.007859171,0.001142108,0.0009813518,0.002461998,0.003101939,0.006163177,0.002160207,0.002789503,0.006358836],"category_scores_gemma":[0.01526719,0.001032632,0.00276029,0.001768256,0.009293745,0.01713432,0.005660781,0.007193434,0.00121587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003750775,"about_ca_system_score_gemma":0.002405011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003529987,"about_ca_topic_score_gemma":0.002562527,"domain_scores_codex":[0.9930467,0.003207313,0.000585394,0.001028426,0.00164276,0.0004893912],"domain_scores_gemma":[0.9895552,0.007278435,0.0006204261,0.0007551712,0.001374804,0.0004160743],"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":[0.00001048996,0.000006913117,0.00005618725,0.0000386432,0.000009050399,0.00007176227,0.0002769043,0.0009621512,0.0001217277,0.995294,0.0006481221,0.002503959],"study_design_scores_gemma":[0.00001115867,0.000006881103,0.00003395128,0.00002653867,0.00001311718,0.00007840804,0.00006376182,0.006561679,0.0001850912,0.9874383,0.005569653,0.00001156412],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009697639,0.001760416,0.9108205,0.01048216,0.0003317991,0.000123983,0.0005907294,0.0005571225,0.06563563],"genre_scores_gemma":[0.6012589,0.002007985,0.370268,0.003454152,0.001525937,0.0005538815,0.000748908,0.0002486595,0.01993364],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007859171,"threshold_uncertainty_score":0.04156375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05277767543155166,"score_gpt":0.2654178339863315,"score_spread":0.2126401585547798,"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."}}