From Classical to Non-monotonic Deontic Logic Using ASPIC $$^+$$

Dong, Huimin; Liao, Beishui; Markovich, Réka; Torre, Leendert van der

doi:10.1007/978-3-662-60292-8_6

Cited by 4 publications

(7 citation statements)

References 13 publications

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“…Here we first introduce the rule-based preferece [18] to give arguments priority. The rule-based preference always preferes strict arguments than the defeasible ones.…”

Section: Preferences Among Argumentsmentioning

confidence: 99%

“…Thus this preference (strictly) prefers B 3 than A 4 in Figure 1.There also other ways of comparing arguments. One is called universal preference, another is called premise-based preference [47,18]. The universal preference prefers every argument the same.…”

Section: Preferences Among Argumentsmentioning

confidence: 99%

“…Basically, chosen two modal logics, strict rules can be defined by the derivations in the lower-bounded logic, while defeasible rules are by those derived in the upper-bounded logic but not the lower-bounded one [18]. This methodology, as argued by Modgil and Prakken [47], is based on certain cognitional or rational criteria.…”

Section: Argumentation-based Logicmentioning

confidence: 99%

“…To answer the first question, we introduce rights and permissions in AI logic as our central concepts for social reasoning. We explain how they interact with prohibitions and obligations in different ways, and how they relate to other social concepts like freedom to act [16,17,18]. Rights and permissions emphasize how social norms empower agents to achieve things they could not achieve by themselves [19,20,5].…”

Section: Introductionmentioning

confidence: 99%

“…In the third question, the omnipresence of conflict and uncertainty in social reasoning leads to the use of formal argumentation [18]. Conflict is not ignored but accepted, and the aim of reasoning is often not only to resolve such conflicts, but also to agree where the agents disagree.…”

Section: Introductionmentioning

confidence: 99%

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Towards AI Logic for Social Reasoning

Dong,

Markovich,

van der Torre

2021

Preprint

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Artificial Intelligence (AI) logic formalizes the reasoning of intelligent agents. In this paper, we discuss how an argumentation-based AI logic could be used also to formalize important aspects of social reasoning. Besides reasoning about the knowledge and actions of individual agents, social AI logic can reason also about social dependencies among agents using the rights, obligations and permissions of the agents. We discuss four aspects of social AI logic. First, we discuss how rights represent relations between the obligations and permissions of intelligent agents. Second, we discuss how to argue about the right-to-know, a central issue in the recent discussion of privacy and ethics. Third, we discuss how a wide variety of conflicts among intelligent agents can be identified and (sometimes) resolved by comparing formal arguments. Importantly, to cover a wide range of arguments occurring in daily life, also fallacious arguments can be represented and reasoned about. Fourth, we discuss how to argue about the freedom to act for intelligent agents. Examples from social, legal and ethical reasoning highlight the challenges in developing social AI logic. The discussion of the four challenges leads to a research program for argumentation-based social AI logic, contributing towards the future development of AI logic.

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“…Here we first introduce the rule-based preferece [18] to give arguments priority. The rule-based preference always preferes strict arguments than the defeasible ones.…”

Section: Preferences Among Argumentsmentioning

confidence: 99%

Section: Preferences Among Argumentsmentioning

confidence: 99%

Section: Argumentation-based Logicmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Towards AI Logic for Social Reasoning

Dong,

Markovich,

van der Torre

2021

Preprint

Self Cite

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Free choice permission, legitimization and relating semantics

Glavaničová

Jarmużek

Klonowski

et al. 2022

Logic Journal of the IGPL

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In this paper, we apply relating semantics to the widely discussed problem of free choice between permitted actions or situations in normative systems. Leaving aside contexts in which the free choice principle is obviously unacceptable (weak permission understood as an absence of prohibition) or uncontroversially valid (strong permission within systems with a closed repertoire of actions or situations), we concentrate on free choice for explicit permissions. In order to construct a formal representation of explicit permissions, we introduce a special constant, $\texttt {permit}$, which is analogous to the constant $\texttt {violation}$ used in the Andersonian–Kangerian approach to deontic logic with respect to prohibition and obligation. Consequently, we define a permission operator on the basis of the $\texttt {permit}$ constant and a relation of legitimization. The general idea is that $P \varphi $ is true if and only if $\texttt {permit}$ is true, which means that a permission is actually issued and $\varphi $ is legitimized by $\texttt {permit}$. The intuitive notion of legitimization is formally represented by an operator of relating implication: a non-classical implication that is semantically defined by adding a constraint to the classical meaning of implication to the effect that arguments are related by a special relation. The properties of this relation are based on an informal, intuitive meaning of legitimization and determine the properties of the permission operator. We show that the resulting permission operator possesses the free choice property and avoids certain unwanted consequences that follow from alternative approaches.

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Logic of defeasible permission and its dynamics

Dong

2021

Journal of Logic and Computation

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This paper develops a deontic logic for defeasible permission and studies norm change in various updated semantics. When one grants that $\varphi $ or $\psi $ is permitted, normally, it goes together with the conjunction of a permission of $\varphi $ and that of $\psi $. In the monotonic reasoning on this permission, a permission of $\varphi $ leads to a permission of $\varphi $ and $\psi $; however, if a prohibition of $\psi $ is introduced, we get into trouble. We face a paradox of free choice permission. Many solutions have been proposed, but a systematic account of handling norm change is still needed. This paper first introduces the notion of normality to develop a sound and complete deontic logic for defeasible permission, which can be used to analyse several notions in natural language and in game theory. Further, following Lewis’ idea of norm change, a systematic way to capture various dynamics for updating permission and obligation is proposed.

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From Classical to Non-monotonic Deontic Logic Using ASPIC $$^+$$

Cited by 4 publications

References 13 publications

Towards AI Logic for Social Reasoning

Towards AI Logic for Social Reasoning

Free choice permission, legitimization and relating semantics

Logic of defeasible permission and its dynamics

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