248 research outputs found
Stable Normative Explanations
No full textModelling the concept of explanation is a central matter in AI systems, as it provides methods for developing eXplainable AI (XAI). When explanation applies to normative reasoning, XAI aims at promoting normative trust in the decisions of AI systems: in fact, such a trust depends on understanding whether systems predictions correspond to legally compliant scenarios. This paper extends to normative reasoning a work by Governatori et al. (2022) on the notion of stable explanations in a non-monotonic setting: when an explanation is stable, it can be used to infer the same normative conclusion independently of other facts that are found afterwards
From Defeasible Logic to Counterfactual Reasoning
No full textCounterfactual reasoning has been the subject of extensive study in philosophy, logics, and AI. The connection between counterfactual reasoning and theory revision is well-known since Ramsey's intuition, according to which "to find out whether the counterfactual `if A were true, then B would be true' is satisfied in a state S, change the state S minimally to include A, and test whether B is satisfied in the resulting state". In this paper we study how to model this idea in Defeasible Logic for devising logics for counterfactual reasoning and suitable selection function models
Computing Defeasible Meta-logic
No full textWe provide a framework for computing meta-logic within non monotonic reasonin
Business process data compliance
No full textMost approaches to business process compliance are restricted to the analysis of the structure of processes. It has been argued that full regulatory compliance requires information on not only the structure of processes but also on what the tasks in a process do. To this end Governatori and Sadiq [2007] proposed to extend business processes with semantic annotations. We propose a methodology to automatically extract one kind of such annotations; in particular the annotations related to the data schema and templates linked to the various tasks in a business process.Full Tex
Applications of linear defeasible logic: Combining resource consumption and exceptions to energy management and business processes
No full textLinear Logic and Defeasible Logic have been adopted to formalise different features of knowledge representation: consumption of resources, and non monotonic reasoning in particular to represent exceptions. Recently, a framework to combine sub-structural features, corresponding to the consumption of resources, with defeasibility aspects to handle potentially conflicting information, has been discussed in literature, by some of the authors. Two applications emerged that are very relevant: energy management and business process management. We illustrate a set of guide lines to determine how to apply linear defeasible logic to those context
Inference to the Stable Explanations
No full textThe process of explaining a piece of evidence by constructing a set of assumptions that are a good explanation for that evidence is ubiquitous in real-life (e.g. in legal systems). In this paper, we introduce, discuss, and formalise the notion of stable explanations in a non-monotonic setting. We show how, while applying it to the process of (1) computing a set of literals able to (2) derive a conclusion (3) from a set of defeasible rules, we obtain a restricted version of the notion of abduction. This is both interesting and useful: when an explanation for a given conclusion is stable, it can, in fact, be used to infer the same conclusion independently of other pieces of evidence that are found afterwards
Modelling legal knowledge for GDPR compliance checking
No full textIn the last fifteen years, Semantic Web technologies have been successfully applied to the legal domain. By composing all those techniques and theoretical methods, we propose an integrated framework for modelling legal documents and legal knowledge to support legal reasoning, in particular checking compliance. This paper presents a proof-of-concept applied to the GDPR domain, with the aim to detect infringements of privacy compulsory norms or to prevent possible violations using BPMN and Regorous engine
Advancements in Resource-Driven Substructural Defeasible Logic
No full textLinear Logic and Defeasible Logic have been adopted to formalise different features of knowledge representation: consumption of resources and reasoning with exceptions. We propose a framework to combine sub-structural features, corresponding to the consumption of resources, with defeasibility aspects to handle potentially conflicting information, and we discuss the design choices
Deontic meta-rules
No full textThe use of meta-rules in logic, i.e., rules whose content includes other rules, has recently gained attention in the setting of non-monotonic reasoning: a first logical formalisation and efficient algorithms to compute the (meta)-extensions of such theories were proposed in Olivieri et al. (2021, Computing defeasible meta-logic. In JELIA 2021, LNCS, vol. 12678, pp. 69-84. Springer.). This work extends such a logical framework by considering the deontic aspect. The resulting logic will not just be able to model policies but also tackle well-known aspects that occur in numerous legal systems. The use of Defeasible Logic to model meta-rules in the application area we just alluded to has been investigated. Within this line of research, the study mentioned above was not focusing on the general computational properties of meta-rules.This study fills this gap with two major contributions. First, we introduce and formalise two variants of Defeasible Deontic Logic (DDL) with meta-rules to represent (i) defeasible meta-theories with deontic modalities and (ii) two different types of conflicts among rules: Simple Conflict DDL and Cautious Conflict DDL. Second, we advance efficient algorithms to compute the extensions for both variants
Computing Private International Law
No full textThis paper develops a new comprehensive computational framework for reasoning about private international law that encompasses the reasoning patterns modeled by previous works [3,8,9]. The framework is a multi-modal extension of [10] preserving some nice properties of the original system, including some efficient algorithms to compute the extensions of normative theories representing legal systems
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