Defeasible Deontic Logic: Arguing about Permission and Obligation

in IfCoLog Journal of Logics and Their Applications (2022), 9(4), 957-1018

Defeasible deontic logic uses techniques from non-monotonic logic to address various challenges in normative reasoning, such as prima facie permissions and obligations, moral dilemmas, deontic detachment ... [more ▼]

Defeasible deontic logic uses techniques from non-monotonic logic to address various challenges in normative reasoning, such as prima facie permissions and obligations, moral dilemmas, deontic detachment, contrary-to-duty reasoning and legal interpretation. In this article, we use formal argumentation to design defeasible deontic logics, based on two classical deontic logics. In particular, we use the ASPIC+ structured argumentation theory to define non-monotonic variants of well-understood monotonic modal logics. We illustrate the ASPIC+-based approach and the resulting defeasible deontic logics using argumentation about strong permission. [less ▲]

Detachment in Normative Systems: Examples, Inference Patterns, Properties

in IfCoLog Journal of Logics and Their Applications (2022), 9(4), 1019-1062

There is a variety of ways to reason with normative systems. This partly reflects a variety of semantics developed for deontic logic, such as traditional semantics based on possible worlds, or alternative ... [more ▼]

There is a variety of ways to reason with normative systems. This partly reflects a variety of semantics developed for deontic logic, such as traditional semantics based on possible worlds, or alternative semantics based on algebraic methods, explicit norms or techniques from non-monotonic logic. This diversity raises the question how these reasoning methods are related, and which reasoning method should be chosen for a particular application. In this paper we discuss the use of examples, inference patterns, and more abstract properties. First, benchmark examples can be used to compare ways to reason with normative systems. We give an overview of several benchmark examples of normative reasoning and deontic logic: van Fraassen’s paradox, Forrester’s paradox, Prakken and Sergot’s cottage regulations, Jeffrey’s disarmament example, Chisholm’s paradox, Makinson’s Möbius strip, and Horty’s priority examples. Moreover, we distinguish various interpretations that can be given to these benchmark examples, such as consistent interpretations, dilemma interpretations, and violability interpretations. Second, inference patterns can be used to compare different ways to reason with normative systems. Instead of analysing the benchmark examples semantically, as it is usually done, in this paper we use inference patterns to analyse them at a higher level of abstraction. We discuss inference patterns reflecting typical logical properties such as strengthening of the antecedent or weakening of the consequent. Third, more abstract properties can be defined to compare different ways to reason with normative systems. To define these more abstract properties, we first present a formal framework around the notion of detachment. Some of the ten properties we introduce are derived from the inference patterns, but others are more abstract: factual detachment, violation detection, substitution, replacements of equivalents, implication, para-consistency, conjunction, factual monotony, norm monotony, and norm induction. We consider these ten properties as desirable for a reasoning method for normative systems, and thus they can be used also as requirements for the further development of formal methods for normative systems and deontic logic. [less ▲]

Normative Change: An AGM Approach

in IfCoLog Journal of Logics and Their Applications (2022), 9(4), 787-852

Studying normative change has practical and theoretical interests. Changing legal rules poses interpretation problems to determine the content of legal rules. The question of interpretation is tightly ... [more ▼]

Studying normative change has practical and theoretical interests. Changing legal rules poses interpretation problems to determine the content of legal rules. The question of interpretation is tightly linked to those of determining the validity and the ability to produce effects of legal rules. Different formal models of normative change seem better suited to capture these dimensions: the dimension of validity appears to be better captured by the AGM approach, whereas syntactic methods are better suited to model how rules’ effects are blocked or enabled. Historically, the AGM approach of belief revision (on which we focus in this chapter) was the first formal model of normative change. We provide a survey on the AGM approach along with the main criticisms made to it. We then turn to a formal analysis of normative change that combines AGM theory and input/output logic, allowing for a clear distinction between norms and obligations. Our approach addresses some of the difficulties of normative change, like the combination of constitutive and regulative rules (and the normative conflicts that may arise from such a combination), the revision and contraction of normative systems, as well as the contraction of normative systems that combine sets of constitutive and regulative rules. We end our chapter by highlighting and discussing some challenges and open problems of normative change in the AGM approach. [less ▲]

Base Argumentation as an Abstraction of Deductive Argumentation

in Baroni, Pietro; Benzmüller, Christoph; Wáng, Yì N. (Eds.) Logic and Argumentation - 4th International Conference, CLAR 2021, Hangzhou, China, October 20-22, 2021, Proceedings (2021)

Base argumentation is a logic-based instantiation of abstract argumentation. Each base argument is a subset of the given knowledge base. In this paper, we show that base argumentation satisfies some ... [more ▼]

Base argumentation is a logic-based instantiation of abstract argumentation. Each base argument is a subset of the given knowledge base. In this paper, we show that base argumentation satisfies some rationality postulates, and that base argumentation is equivalent to deductive argumentation under complete semantics. Due to its simplicity, base argumentation can be seen as an abstraction of deductive argumentation. [less ▲]

Towards AI Logic for Social Reasoning

E-print/Working paper (2021)

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 ... [more ▼]

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. [less ▲]

Expectation: Personalized Explainable Artificial Intelligence for Decentralized Agents with Heterogeneous Knowledge

in Calvaresi, Davide; Najjar, Amro; Winikoff, Michael (Eds.) et al Explainable and Transparent AI and Multi-Agent Systems - Third International Workshop, EXTRAAMAS 2021, Virtual Event, May 3-7, 2021, Revised Selected Papers (2021)

Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies to interpret and explain machine learning (ML) predictors. To date, many initiatives have been proposed ... [more ▼]

Explainable AI (XAI) has emerged in recent years as a set of techniques and methodologies to interpret and explain machine learning (ML) predictors. To date, many initiatives have been proposed. Nevertheless, current research efforts mainly focus on methods tailored to specific ML tasks and algorithms, such as image classification and sentiment analysis. However, explanation techniques are still embryotic, and they mainly target ML experts rather than heterogeneous end-users. Furthermore, existing solutions assume data to be centralised, homogeneous, and fully/continuously accessible—circumstances seldom found altogether in practice. Arguably, a system-wide perspective is currently missing. The project named “Personalized Explainable Artificial Intelligence for Decentralized Agents with Heterogeneous Knowledge” (Expectation) aims at overcoming such limitations. This manuscript presents the overall objectives and approach of the Expectation project, focusing on the theoretical and practical advance of the state of the art of XAI towards the construction of personalised explanations in spite of decentralisation and heterogeneity of knowledge, agents, and explainees (both humans or virtual). To tackle the challenges posed by personalisation, decentralisation, and heterogeneity, the project fruitfully combines abstractions, methods, and approaches from the multi-agent systems, knowledge extraction / injec- tion, negotiation, argumentation, and symbolic reasoning communities. [less ▲]

Populating legal ontologies using semantic role labeling

in Artificial Intelligence and Law (2021), 29(2), 171-211

This article seeks to address the problem of the ‘resource consumption bottleneck’ of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction ... [more ▼]

This article seeks to address the problem of the ‘resource consumption bottleneck’ of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction system to extract definitions and norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in a legal document management system. [less ▲]

LogiKEy Workbench: Deontic Logics, Logic Combinations and Expressive Ethical and Legal Reasoning (Isabelle/HOL Dataset)

in Data in Brief (2020), 33

The LogiKEy workbench and dataset for ethical and legal reasoning is presented. This workbench simultaneously supports development, experimentation, assessment and deployment of formal logics and ethical ... [more ▼]

The LogiKEy workbench and dataset for ethical and legal reasoning is presented. This workbench simultaneously supports development, experimentation, assessment and deployment of formal logics and ethical and legal theories at different conceptual layers. More concretely, it comprises, in form of a dataset (Isabelle/HOL theory files), formal encodings of multiple deontic logics, logic combinations, deontic paradoxes and normative theories in the higher-order proof assistant system Isabelle/HOL. The data were acquired through application of the LogiKEy methodology, which supports experimentation with different normative theories, in different application scenarios, and which is not tied to specific logics or logic combinations. Our workbench consolidates related research contributions of the authors and it may serve as a starting point for further studies and experiments in flexible and expressive ethical and legal reasoning. It may also support hands-on teaching of non-trivial logic formalisms in lecture courses and tutorials. [less ▲]

Intention as commitment toward time

in Artificial Intelligence and Law (2020), 283

In this paper we address the interplay among intention, time, and belief in dynamic environments. The first contribution is a logic for reasoning about intention, time and belief, in which assumptions of ... [more ▼]

In this paper we address the interplay among intention, time, and belief in dynamic environments. The first contribution is a logic for reasoning about intention, time and belief, in which assumptions of intentions are represented by preconditions of intended actions. Intentions and beliefs are coherent as long as these assumptions are not violated, i.e. as long as intended actions can be performed such that their preconditions hold as well. The second contribution is the formalization of what-if scenarios: what happens with intentions and beliefs if a new (possibly conflicting) intention is adopted, or a new fact is learned? An agent is committed to its intended actions as long as its belief-intention database is coherent. We conceptualize intention as commitment toward time and we develop AGM-based postulates for the iterated revision of belief-intention databases, and we prove a Katsuno-Mendelzon-style representation theorem. [less ▲]

A bimodal simulation of defeasibility in thenormative domain

in CEUR Workshop Proceedings (2020)

In the present work we illustrate how two sorts of defeasiblereasoning that are fundamental in the normative domain, that is, reasoning about exceptions and reasoning about violations, can be simulated ... [more ▼]

In the present work we illustrate how two sorts of defeasiblereasoning that are fundamental in the normative domain, that is, reasoning about exceptions and reasoning about violations, can be simulated via monotonic propositional theories based on a bimodal language with primitive operators representing knowledge and obligation. The proposed theoretical framework paves the way to using native theorem provers for multimodal logic, such as MleanCoP, in order to automate normative reasoning. [less ▲]