On trivalent logics, probabilistic weak deduction theorems, and a general import-export principle

IF 5.1 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Pub Date : 2024-09-23 DOI:10.1016/j.artint.2024.104229
Angelo Gilio , David E. Over , Niki Pfeifer , Giuseppe Sanfilippo
{"title":"On trivalent logics, probabilistic weak deduction theorems, and a general import-export principle","authors":"Angelo Gilio ,&nbsp;David E. Over ,&nbsp;Niki Pfeifer ,&nbsp;Giuseppe Sanfilippo","doi":"10.1016/j.artint.2024.104229","DOIUrl":null,"url":null,"abstract":"<div><div>In this paper we first recall some results for conditional events, compound conditionals, conditional random quantities, p-consistency, and p-entailment. We discuss the equivalence between conditional bets and bets on conditionals, and review de Finetti's trivalent analysis of conditionals. But we go beyond de Finetti's early trivalent logical analysis and his later ideas, aiming to take his proposals to a higher level. We examine two recent articles that explore trivalent logics for conditionals and their definitions of logical validity and compare them with the approach to compound conditionals introduced by Gilio and Sanfilippo within the framework of conditional random quantities. As we use the notion of p-entailment, the full deduction theorem does not hold. We prove a Probabilistic Weak Deduction Theorem for conditional events. After that we study some variants of it, with further results, and we present several examples. Moreover, we illustrate how to derive new inference rules related to selected Aristotelian syllogisms. We focus on iterated conditionals and the invalidity of the Import-Export principle in the light of our Probabilistic Weak Deduction Theorem. We use the inference from a disjunction, <em>A or B</em>, to the conditional, <em>if not-A then B</em>, as an example to show the invalidity of this principle. We introduce a General Import-Export principle by examining examples and counterexamples. In particular, when considering the inference rules of System P, we find that a General Import-Export principle is satisfied, even if the assumptions of the Probabilistic Weak Deduction Theorem do not hold. We also deepen further aspects related to p-entailment and p-consistency. Finally, we briefly discuss some related work relevant to AI.</div></div>","PeriodicalId":8434,"journal":{"name":"Artificial Intelligence","volume":"337 ","pages":"Article 104229"},"PeriodicalIF":5.1000,"publicationDate":"2024-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0004370224001656","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper we first recall some results for conditional events, compound conditionals, conditional random quantities, p-consistency, and p-entailment. We discuss the equivalence between conditional bets and bets on conditionals, and review de Finetti's trivalent analysis of conditionals. But we go beyond de Finetti's early trivalent logical analysis and his later ideas, aiming to take his proposals to a higher level. We examine two recent articles that explore trivalent logics for conditionals and their definitions of logical validity and compare them with the approach to compound conditionals introduced by Gilio and Sanfilippo within the framework of conditional random quantities. As we use the notion of p-entailment, the full deduction theorem does not hold. We prove a Probabilistic Weak Deduction Theorem for conditional events. After that we study some variants of it, with further results, and we present several examples. Moreover, we illustrate how to derive new inference rules related to selected Aristotelian syllogisms. We focus on iterated conditionals and the invalidity of the Import-Export principle in the light of our Probabilistic Weak Deduction Theorem. We use the inference from a disjunction, A or B, to the conditional, if not-A then B, as an example to show the invalidity of this principle. We introduce a General Import-Export principle by examining examples and counterexamples. In particular, when considering the inference rules of System P, we find that a General Import-Export principle is satisfied, even if the assumptions of the Probabilistic Weak Deduction Theorem do not hold. We also deepen further aspects related to p-entailment and p-consistency. Finally, we briefly discuss some related work relevant to AI.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
论三价逻辑、概率弱演绎定理和一般导入导出原理
在本文中,我们首先回顾条件事件、复合条件、条件随机量、p 一致性和 p 尾数的一些结果。我们讨论了条件投注和条件投注之间的等价性,并回顾了德-菲尼提对条件的三价分析。但我们超越了德菲内蒂早期的三价逻辑分析和他后来的观点,旨在将他的提议提升到更高的层次。我们研究了最近两篇探讨条件的三价逻辑及其逻辑有效性定义的文章,并将它们与吉里奥和桑菲菲利波在条件随机量框架内引入的复合条件的方法进行了比较。由于我们使用 p-entailment 概念,完全演绎定理并不成立。我们证明了条件事件的概率弱演绎定理。之后,我们研究了它的一些变体,并给出了进一步的结果和几个例子。此外,我们还说明了如何推导出与选定的亚里士多德三段论相关的新推理规则。根据我们的概率弱演绎定理,我们将重点放在迭代条件和导入导出原则的无效性上。我们以从析取条件 A 或 B 到条件 If not-A then B 的推理为例,说明该原则的无效性。我们通过研究实例和反例,介绍了一般导入导出原理。特别是,在考虑系统 P 的推理规则时,我们发现即使概率弱演绎定理的假设不成立,一般导入导出原则也是满足的。我们还进一步深化了与 P 尾数和 P 一致性相关的方面。最后,我们简要讨论了一些与人工智能相关的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Artificial Intelligence
Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
11.20
自引率
1.40%
发文量
118
审稿时长
8 months
期刊介绍: The Journal of Artificial Intelligence (AIJ) welcomes papers covering a broad spectrum of AI topics, including cognition, automated reasoning, computer vision, machine learning, and more. Papers should demonstrate advancements in AI and propose innovative approaches to AI problems. Additionally, the journal accepts papers describing AI applications, focusing on how new methods enhance performance rather than reiterating conventional approaches. In addition to regular papers, AIJ also accepts Research Notes, Research Field Reviews, Position Papers, Book Reviews, and summary papers on AI challenges and competitions.
期刊最新文献
Lifted action models learning from partial traces Human-AI coevolution Editorial Board Separate but equal: Equality in belief propagation for single-cycle graphs Generative models for grid-based and image-based pathfinding
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1