How to model contrary-to-duty with GCP-nets

IF 1.9 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Intelligenza Artificiale Pub Date : 2022-12-27 DOI:10.3233/ia-221057
Andrea Loreggia, Roberta Calegari, E. Lorini, Francesca Rossi, G. Sartor
{"title":"How to model contrary-to-duty with GCP-nets","authors":"Andrea Loreggia, Roberta Calegari, E. Lorini, Francesca Rossi, G. Sartor","doi":"10.3233/ia-221057","DOIUrl":null,"url":null,"abstract":"Preferences are ubiquitous in our everyday life. They are essential in the decision making process of individuals. Recently, they have also been employed to represent ethical principles, normative systems or guidelines. In this work we focus on a ceteris paribus semantics for deontic logic: a state of affairs where a larger set of respected prescriptions is preferable to a state of affairs where some are violated. Conditional preference networks (CP-nets) are a compact formalism to express and analyse ceteris paribus preferences, with some desirable computational properties. In this paper, we show how deontic concepts (such as contrary-to-duty obligations) can be modeled with generalized CP-nets (GCP-nets) and how to capture the distinction between strong and weak permission in this formalism. To do that, we leverage on an existing restricted deontic logic that will be mapped into conditional preference nets.","PeriodicalId":42055,"journal":{"name":"Intelligenza Artificiale","volume":"16 1","pages":"185-198"},"PeriodicalIF":1.9000,"publicationDate":"2022-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Intelligenza Artificiale","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/ia-221057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0

Abstract

Preferences are ubiquitous in our everyday life. They are essential in the decision making process of individuals. Recently, they have also been employed to represent ethical principles, normative systems or guidelines. In this work we focus on a ceteris paribus semantics for deontic logic: a state of affairs where a larger set of respected prescriptions is preferable to a state of affairs where some are violated. Conditional preference networks (CP-nets) are a compact formalism to express and analyse ceteris paribus preferences, with some desirable computational properties. In this paper, we show how deontic concepts (such as contrary-to-duty obligations) can be modeled with generalized CP-nets (GCP-nets) and how to capture the distinction between strong and weak permission in this formalism. To do that, we leverage on an existing restricted deontic logic that will be mapped into conditional preference nets.
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
如何使用GCP网络进行违背职责的建模
偏好在我们的日常生活中无处不在。它们在个人决策过程中至关重要。最近,它们也被用来代表伦理原则、规范体系或指导方针。在这项工作中,我们专注于道义逻辑的一个等价语义:一种更大的受尊重的处方集比一些被违反的情况更可取的情况。条件偏好网络(CP nets)是一种表达和分析同一偏好的紧凑形式,具有一些理想的计算性质。在本文中,我们展示了如何用广义CP网(GCP网)对义务概念(如违背义务)进行建模,以及如何在这种形式中捕捉强许可和弱许可之间的区别。为了做到这一点,我们利用了现有的限制道义逻辑,该逻辑将被映射到条件偏好网络中。
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
Intelligenza Artificiale
Intelligenza Artificiale COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
3.50
自引率
6.70%
发文量
13
期刊最新文献
Special Issue NL4AI 2022: Workshop on natural language for artificial intelligence User-centric item characteristics for personalized multimedia systems: A systematic review Combining human intelligence and machine learning for fact-checking: Towards a hybrid human-in-the-loop framework A framework for safe decision making: A convex duality approach Grounding End-to-End Pre-trained architectures for Semantic Role Labeling in multiple languages
×
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