تقرير
Belief Revision from Probability
| العنوان: | Belief Revision from Probability |
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| المؤلفون: | Goodman, Jeremy, Salow, Bernhard |
| المصدر: | EPTCS 379, 2023, pp. 308-317 |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Artificial Intelligence, Computer Science - Logic in Computer Science |
| الوصف: | In previous work ("Knowledge from Probability", TARK 2021) we develop a question-relative, probabilistic account of belief. On this account, what someone believes relative to a given question is (i) closed under entailment, (ii) sufficiently probable given their evidence, and (iii) sensitive to the relative probabilities of the answers to the question. Here we explore the implications of this account for the dynamics of belief. We show that the principles it validates are much weaker than those of orthodox theories of belief revision like AGM, but still stronger than those valid according to the popular Lockean theory of belief, which equates belief with high subjective probability. We then consider a restricted class of models, suitable for many but not all applications, and identify some further natural principles valid on this class. We conclude by arguing that the present framework compares favorably to the rival probabilistic accounts of belief developed by Leitgeb and by Lin and Kelly. Comment: In Proceedings TARK 2023, arXiv:2307.04005 |
| نوع الوثيقة: | Working Paper |
| DOI: | 10.4204/EPTCS.379.25 |
| URL الوصول: | http://arxiv.org/abs/2307.05632 |
| رقم الأكسشن: | edsarx.2307.05632 |
| قاعدة البيانات: | arXiv |
| DOI: | 10.4204/EPTCS.379.25 |
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