Beyond the Rule Representation of Norms: Norms as Social Objects

Deontic Logic in Computer Science, 2002

standard treatment of these notions in deontic logic. Firstly, we propose that instantiated norms be treated asindividual, identified entities - that is, variables that can be quantified over - rather than simply as logicaloperators as in Standard Deontic Logic. This allows us to refer to specific instances of obligations,permissions, and prohibitions. We explain why we believe that norms take, as

The Review of Socionetwork Strategies

The paper at hand introduces and discusses a diagrammatic method to represent legal norms first developed by the second author. It is shown how this method can be used to represent not only norms and argument forms originating from classic legal methodology (legal subsumption, analogy, appeal to the contrary), but also more complex legal-theoretical phenomena, especially legal antinomies. Beyond its didactic virtues, the diagram is a useful theoretical tool for investigating how norms interact with each other and how singular actions can be considered as satisfying or violating a given norm.

Phenomenology & Mind, N. 19, 2020

The essay addresses the debates about the ontology of norms considering the case of accounting for customary norms. It undertakes and defends a stance in favor of a semantic ontology by developing a framework for the explanation of norms as abstract objects and their linking with social facts to be identified in categories like "customary", "enacted", "legal", "grammatical", and so on. Furthermore, the work addresses the rival conceptions (pragmatic and eclectic) by showing the specific impossibility that these face for giving a satisfactory account on customary norms. The inquiry concludes by exploring some possible insights from the philosophy of mind to explain the conceptual nature of norms as mental representations.

The widely observable frequent changes of norms in many normative systems existent in different countries stimulated the research regarding the invention of models used to represent the dynamics of norms. The models concern norms expressed in the form of legal provisions. The application of the event calculus appeared to be a suitable way to model the considered dynamics ([1–3]). According to this approach the authors designed a model ([4]) on the basis of which the changes of legal provisions in time can be handled in a relevant knowledge base. The main purpose of this knowledge base is to support the task of searching for the current version of the provisions. As to the events handling procedure, it is necessary that the knowledge base relevant to the LPDModel should contain the data concerned with all the events, both these, which are passed and also the chronologically ordered list of the forthcoming ones. The list of incoming events must contain the limitary events of the durative actions which are under execution. Also, this list holds the events concerning the promulgation of new or amending statutes. It is worth noticing that the process of the retrieval of the current version of a provision can be done in an efficient way due to the special index, which was introduced to the LPDModel-based knowledge base. It contains the mnemonic names for the basic provisions and enables their browsing. The current textual version of the required basic provisions is retrieved accompanied by the provisions that are actually structurally related to it. The aim of the next section is to describe the structure of the LPDModel - based knowledge base.

2016

In this paper we will introduce a method for creating computational models of normative systems deduced from sources of norms in natural language. The authors show how to make formal interpretations of normative sources in natural language that result in a computational model, which includes explicit references to all sentences of sources of norms that are considered relevant by the interpreters to constitute a computational model. The models produced can easily be held in sync with these sources. The method presented is focused on the translation of laws in natural language into an executable computational form that can be easily validated by legal experts that have to decide on the desired interpretation of the source text. The model is tested in a prototype of a reasoner build in a newly developed domain specific language: FLINT. The model is based on Hohfeld’s fundamental legal concepts.

1996

2023

Recording and documenting human and AI-driven normative decisionmaking processes has so far been highly challenging. We focus on the challenge of normative coordination: the process by which stakeholders in a community understand and agree what norms they abide by. Our aim is to develop and formalize the FLINT language, which allows a high-level description of normative systems. FLINT enables legal experts to agree on norms, while also serving as a basis for technical implementation. Our contribution consists of the development of an ontology for FLINT and its RDF/OWL implementation which we have made openly accessible. We designed the ontology on the basis of competency questions. Additionally, we validated the ontology by modeling example cases and using the ontology's data model in software tooling.

Artificial Intelligence and Law, 2004

This article describes an ontological model of norms. The basic assumption is that a substantial part of a legal system is grounded on the concept of agency. Since a legal system aims at regulating a society, then its goal can be achieved only by affecting the behaviour of the members of the society. We assume that a society is made up of agents (which can be individuals, institutions, software programs, etc.), that agents have beliefs, goals and preferences, and that they commit to intentions in order to choose a line of behaviour. The role of norms, within a legal system, is to specify how and when the chosen behaviour agrees with the basic principles of the legal system. In this article, we show how a model based on plans can be the basis for the ontological representation of norms, which are expressed as constraints on the possible plans an agent may choose to guide its behaviour. Moreover, the paper describes how the proposed model can be linked to the upper level of a philosophically well-founded ontology (DOLCE); in this way, the model is set in a wider perspective, which opens the way to further developments.

Although legal informatics is on the periphery of jurisprudence, it can make a significant impact on the centre in respect of legal dogmatics. We believe that the impact from legal informatics can be reached through situational legal visualisation and situational terms, for example, by correcting the boundaries of legal terms. The latter is the subject matter of legal theory and hence contributes to the centre of jurisprudence. This paper makes analogy between Begriffsjurisprudenz in the nineteenth century and legal ontologies of the present, and stresses a situational treatment of law in addition to a normative one. Therefore both situational contents and institutional contents are important when representing legal semantics within legal informatics. However, the differences between legal norms, texts and documents have to be taken into account. Legal norms are interpretative products whereas legal documents are tangible products and are represented according to documentary rules. ...

International Journal of Human-Computer Studies, 1999

Note on formatting: The paper, especially the appendix, contains formulas with special formatting. To distinguish formulas from normal text a different font is used, as in the formula OCCURS(event). In formulas, the specific use of ordinary and italic characters is meaningful, as in OCCURS(event). Also the specific use of uppercase characters, lowercase characters, and small capitals is meaningful, as in Occurs(event), occurs(event), and OCCURS(event). Some ordinary set-theoretical symbols are used, as in State_of_affairs ∈ REPRESENTATION and STATES_OF_AFFAIRS ⊆ TERMS. The symbol ℘ in ℘(RULES) is an uppercase 'curly' P as used for denoting the power set of a set.