This paper is concerned with the goal of maintaining legal information and compliance systems: the ‘resource consumption bottleneck’ of creating semantic technologies manually. The use of automated information extraction techniques could significantly reduce this bottleneck. The research question of this paper is: How to address the resource bottleneck problem of creating specialist knowledge management systems? In particular, how to semi-automate the extraction of norms and their elements to populate legal ontologies? This paper shows that the acquisition paradox can be addressed by combining state-of-the-art general-purpose NLP modules with pre- and post-processing using rules based on domain knowledge. It describes a Semantic Role Labeling based information extraction system to extract 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 legal document management systems such as Eunomos (Boella et al., 2016).

People with autism have idiosyncratic sensory experiences, which may impact on how they live the “spaces” of their everyday life. Starting from an investigation of their conception and experience of “secure places,” we defined a series of user requirements for designing technology that supports their everyday movements in the urban environment. On the basis of such requirements, we developed an interactive system that leverages crowdsourcing mechanisms to map places that are perceived as secure by the population with autism.

This paper describes the preliminary results of a project aimed to support people with autism in finding city places that match their "sensorial" preferences and aversions. Through a participatory design approach, we designed an interactive map that collects sensorial data about the urban environment exploiting crowdsourcing mechanisms.

In April 2018, under the auspices of the POR-FESR 2014-2020 program of Italian Piedmont Region, the Turin's Centre on High-Performance Computing for Artificial Intelligence (HPC4AI) was funded with a capital investment of 4.5M€ and it began its deployment. HPC4AI aims to facilitate scientific research and engineering in the areas of Artificial Intelligence and Big Data Analytics. HPC4AI will specifically focus on methods for the on-demand provisioning of AI and BDA Cloud services to the regional and national industrial community, which includes the large regional ecosystem of Small-Medium Enterprises (SMEs) active in many different sectors such as automotive, aerospace, mechatronics, manufacturing, health and agrifood.

Scaling and visualization theories about traditional maps can be extended to digital maps in order to develop web applications using maps as information management systems, data viewer and recommender systems. Starting from current limitations of web application using maps, we outline an alternative approach based on building an indexing system connecting scales and contents, on fixing visualization and styling rules, and attributing an active role to the user in defining goals, area of interest and related contents. This contribution presents the first steps towards a theoretical framework to develop map-based applications where contents are connected to the map entities and the user interactions impact on the status of the map and of the application at the same time.

Cities can be seen as systems of urban artefacts interacting with human activities. Since cities in this sense need to be organized and coordinated, convergences and divergences between the "planned" and the "lived" city have always been of paramount interest in urban planning. The increasing amount of geo big data and the growing impact of Internet of Things (IoT) in contemporary smart city is pushing toward a re-conceptualization of urban systems taking into consideration the complexity of human behaviors. This work contributes to this view by proposing an ontological analysis of urban artefacts and their roles, focusing in particular on the difference between social roles and functional roles through the prism of social practices.

Companies must be able to demonstrate that their way of doing business is compliant with relevant rules and regulations. However, the law often has open texture; it is generic and needs to be interpreted before it can be applied in a specific case. Entrepreneurs generally lack the expertise to engage in the regulatory conversations that make up this interpretation process. In particular for the application domain of technological startups, this leads to legal risks. This research seeks to develop a robust module for legal interpretation. We apply informal logic to bridge the gap between the principles of interpretation in legal theory with the legal rules that determine compliance of business processes. Accordingly, interpretive arguments characterized by argument schemes are applied to business models represented by value modeling (VDML). The specific outcome of the argumentation process (if any) is then summarized into a compliance pattern, in a context-problem-solution format. A case study from copyright law, about an internet television company, shows that the approach is able to express the legal arguments of the case, but is also understandable for the target audience.

This paper presents a unifying text similarity measure (USM) for automated identification of national implementations of European Union (EU) directives. The proposed model retrieves the transposed provisions of national law at a fine-grained level for each article of the directive. USM incorporates methods for matching common words, common sequences of words and approximate string matching. It was used for identifying transpositions on a multilingual corpus of four directives and their corresponding national implementing measures (NIMs) in three different languages : English, French and Italian. We further utilized a corpus of four additional directives and their corresponding NIMs in English language for a thorough test of the USM approach. We evaluated the model by comparing our results with a gold standard consisting of official correlation tables (where available) or correspondences manually identified by domain experts. Our results indicate that USM was able to identify transpositions with average F-score values of 0.808, 0.736 and 0.708 for French, Italian and English Directive-NIM pairs respectively in the multilingual corpus. A comparison with state-of-the-art methods for text similarity illustrates that USM achieves a higher F-score and recall across both the corpora.

This paper presents a concept recognition system for European and national legislation. Current named entity recognition (NER) systems do not focus on identifying concepts which are essential for interpretation and harmonization of European and national law. We utilized the IATE (Inter-Active Terminology for Europe) vocabulary, a state-of-the-art named entity recognition system and Wikipedia to generate an annotated corpus for concept recognition. We applied conditional random fields (CRF) to identify concepts on a corpus of European directives and Statutory Instruments (SIs) of the United Kingdom. The CRF-based concept recognition system achieved an F1 score of 0.71 over the combined corpus of directives and SIs. Our results indicate the usability of a CRF-based learning system over dictionary tagging and state-of-the-art methods.

We propose a domain specific Question Answering system. We deviate from approaching this problem as a Textual Entailment task. We implemented a Memory Network-based Question Answering system which test a Machine's understanding of legal text and identifies whether an answer to a question is correct or wrong, given some background knowledge. We also prepared a corpus of real USA MBE Bar exams for this task. We report our initial result and direction for future works.

This paper investigates the application of text similarity techniques to automatically detect the transposition of European Union (EU) directives into the national law. Currently, the European Commission (EC) resorts to time-consuming and expensive manual methods like conformity checking studies and legal analysis for identifying national transposition measures. We utilize both lexical and semantic similarity techniques and supplement them with knowledge from EuroVoc to identify transpositions. We then evaluate our approach by comparing the results with the correlation tables (gold standard). Our results indicate that both similarity techniques proved to be effective in detecting transpositions. Such systems could be used to identify the transposed provisions by both EC and legal professionals.

In this paper we describe how the EUCases FP7 project is addressing the problem of lifting Legal Open Data to Linked Open Data to develop new applications for the legal information provision market by enriching structurally the documents (first of all with navigable references among legal texts) and semantically (with concepts from ontologies and classification). First we describe the social and economic need for breaking the accessibility barrier in legal information in the EU, then we describe the technological challenges and finally we explain how the EUCases project is addressing them by a combination of Human Language Technologies.

Runtime monitors check the execution of a system under scrutiny against a set of formal specifications describing a prescribed behaviour. The two core properties for monitoring systems are scalability and adaptability. In this paper we show how RuleRunner, our previous neural-symbolic monitoring system, can exploit learning strategies in order to integrate desired deviations with the initial set of specification. The resulting system allows for fast conformance checking and can suggest possible enhanced models when the initial set of specifications has to be adapted in order to include new patterns.

Business Process Management Systems (BPMS) are widely recognized as fundamental component of the IT infrastructure supporting middle-large organization, thanks to their capacity of providing easy-to-read models of how the organization works, and to the capability of enacting these business processes, supporting and monitoring their execution. In this work we present results collected during a feasibility study, that aims to apply BPM concepts to a legal domain: decision and enforcement of preliminary injunctions.

This paper looks at the use of recitals in the interpretation of EU legislation, and mechanisms for connecting them to normative provisions. The purposive approach to the interpretation of EU legislation taken by the European Court of Justice makes frequent references to recitals as helping to establish the purpose of normative provisions. Our research uses a cosine similarity based approach to link articles with relevant provisions to help legal professionals and lay end-users interpret the law. Such support can be used in legal knowledge-based systems.

A recent trend in High-Performance Computation is parallel computing, and the field of Neural Networks is showing impressive improvements in performance, especially with the use of GPU accelerators. In this paper, we use neural networks to improve the performance of Runtime Verification. Runtime verification is used in a variety of domains -from policy enforcement to electronic fraud detection-to automatically check whether a system meets a temporal specification, by observing the output of the system. In this paper, we present a novel run-time monitoring system, RuleRunner, and we exploit results from the Neural-Symbolic Integration area to encode it in a recurrent neural network. The results show that neural networks can perform real-time online runtime verification. Performance was improved by the parallel architecture and the matrix-based implementation with GPU.

In this article we show how to model a range of notions in the context of delegation and revocation applied to security scenarios. We demonstrate how a range of delegation–revocation models and policies may be represented in pictorial form and formally represented in terms of reactive Kripke models and a first-order policy specification language. We translate first-order representations of our reactive Kripke models into an equivalent Answer Set Programming form that enables users to apply flexibly well-defined definitions of predicates to represent their requirements in terms of delegation–revocation policy specification.

João Leite, Paolo Torroni, Thomas Ågotnes, Guido Boella, Leendert van der Torre; Preface to the Special Issue on Computational Logic in Multi-Agent Systems (CLI

In this work we present a working system for automatic classification of text documents into the EuroVoc multilingual thesaurus. EuroVoc contains around 7,000 categories with different levels of specificity. The system relies on a simple approach for the treatment of multi-label texts where each document may have more than one associated category. The classifier is based on the well-known Support Vector Machine algorithm trained using the JRC-Acquis corpus, containing around 23,000 documents labeled with six EuroVoc categories in average. The demonstration scenario will show the ability of the system to classify documents taken on site from the Eur-Lex web portal of the European Union, together with features for visualization and navigation of the texts at different granulatity.

Maintaining regulatory compliance is an increasing area of concern for business. Legal Knowledge Management systems that combine repositories of legislation with legal ontologies can support the work of in-house compliance managers. But there are challenges to overcome, of interpreting legal knowledge and mapping that knowledge onto business processes, and developing systems that can adequately handle the complexity with clarity and ease. In this paper we extend the Legal Knowledge Management system Eunomos to deal with alternative interpretations of norms connecting it with Business Process Management systems. Moreover, we propose a workflow involving the different roles in a company, which takes legal interpretation into account in mapping norms and processes, using Eunomos as a support.

Guido Boella, Pablo Noriega, Gabriella Pigozzi, Harko Verhagen; Introduction to the special issue on NorMAS 2009, Journal of Logic and Computation, Volume

This paper introduces Input/Output Argumentation Frameworks, a novel approach to characterize the behavior of an argumentation framework as a sort of black box exposing a well-defined external interface. As a starting point, we define the novel notion of semantics decomposability and analyze complete, stable, grounded and preferred semantics in this respect. Then we show as a main result that, under grounded, complete, stable and credulous preferred semantics, Input/Output Argumentation Frameworks with the same behavior can be interchanged without affecting the result of semantics evaluation of other arguments interacting with them.

In this paper we present a novel method for the automatic classification of multi-label text documents. In principle, automatic classification of text is usually tackled by supervised Machine Learning techniques like Support Vector Machines (SVM), that typically achieve state-of-the-art accuracy in several domains. Nevertheless, SVM can not handle multi-labeled documents, thus a specific preprocessing of the data is needed. In this paper we present a novel technique for the transformation of multi-label data into mono-label that is able to maintain all the information, allowing the use of standard approaches like SVM. We then evaluate our system using JRC-Acquis-it, a large dataset of italian legislation that has been manually annotated according to EuroVoc, demonstrating the potential of our approach compared to the current state of the art.

In this paper, we consider two drawbacks of Cayrol and Lagasque-Schiex's meta-argumentation theory to model bipolar argumentation frameworks. We consider first the “lost of admissibility” in Dung's sense and second, the definition of notions of attack in the context of a support relation. We show how to prevent these drawbacks by introducing support meta-arguments. Like the model of Cayrol and Lagasque-Schiex, our formalization confirms the use of meta-argumentation to reuse Dung's properties. We do not take a stance towards the usefulness of a support relation among arguments, though we show that if one would like to introduce them, it can be done without extending Dung's theory. Finally, we show how to use meta-argumentation to instantiate an argumentation framework to represent defeasible support. In this model of support, the support relation itself can be attacked.

We introduce and study higher-order coalition logic, a multi modal monadic second-order logic with operators [{x}ψ]φ expressing that the coalition of all agents satisfying ψ(x) can achieve a state in which φ holds. We use neighborhood semantics to model extensive games of perfect information with simultaneous actions and we provide a framework reasoning about agents in the same way as it is reasoning about their abilities. We illustrate higher-order coalition logic to represent and reason about coalition formation and cooperation, we show a more general and expressive way to quantify over coalitions than quantified coalition logic, we give an axiomatization and prove completeness.

In this paper we introduce and discuss five guidelines for the use of normative systems in computer science. We adopt a multiagent systems perspective, because norms are used to coordinate, organize, guide, regulate or control interaction among distributed autonomous systems. They are derived from the computer science literature. From the so-called ‘normchange’ definition of the first workshop on normative multiagent systems in 2005 we derive the guidelines to motivate which definition of normative multiagent system is used, to make explicit why norms are a kind of (soft) constraints deserving special analysis, and to explain why and how norms can be changed at runtime. From the so-called ‘mechanism design’ definition of the second workshop on normative multiagent systems in 2007 we derive the guidelines to discuss the use and role of norms as a mechanism in a game-theoretic setting, and to clarify the role of norms in the multiagent system.

This paper describes the philosophy behind our tool called "Legal Taxonomy Syllabus", the analytical instruments it provides and some case studies. The Legal Taxonomy Syllabus is an ontology based tool designed to annotate and recover multi-lingua legal information and build conceptual dictionaries. The Legal Taxonomy Syllabus allows to build legal dictionaries in a bottom up fashion starting from the annotation of legal terms by legal terminological experts and to let legal ontology engineers refine the resulting taxonomies of concepts. The Legal Taxonomy Syllabus and its analytical tools provide help to lawyers to study the peculiarities of European Union Directives concerning the polysemy of legal terms, and the terminological and conceptual misalignment. By means of two case studies we show how the Legal Taxonomy Syllabus can help the processes of drafting and translating of the Directives.

In this paper is we apply insights from mechanism design to the design of agent interaction protocols. We show how this allows us a more flexible approach to the design of agent interaction protocols. By way of an analysis of a dialogue game from the literature we show how a protocol with many constraints on the moves allowed can be replaced by one in which we relax the rules, but make stronger assumptions on the type of participant that is involved in the dialogue. We can then use techniques from game theory and mechanism design to show that many of the constraints in the original protocol can be derived as properties of rational behavior.

Normative multiagent systems provide agents with abilities to autonomously devise societies and organizations coordinating their behavior via social norms and laws. In this paper, we study how agents negotiate new social norms and when they accept them. We introduce a negotiation model based on what we call the social delegation cycle, which explains the negotiation of new social norms from agent desires in three steps. First, individual agents or their representatives negotiate social goals, then a social goal is negotiated in a social norm, and finally the social norm is accepted by the agents when it leads to fulfillment of the desires the cycle started with. We characterize the allowed proposals during social goal negotiation as mergers of the individual agent desires, and we characterize the allowed proposals during norm negotiation as both joint plans to achieve the social goal (obligations associated with the norm) and the associated sanctions or rewards (a control system associated with the norm). The norm is accepted when the norm is stable in the sense that agents will act according to the norm, and effective in the sense that fulfillment of the norm leads to achievement of the agents' desires. We also compare norm negotiation with contract negotiation and negotiation of the distribution of obligations.

Contracts are used to create new interaction possibilities among agents, and therefore play an important role in the game theoretic analysis of agent interaction. We use normative multiagent systems to model both the contracts and the interactions. In particular, we formalize contracts as systems of regulative and constitutive norms within a larger rule-governed setting and, using recursive modeling, we develop a game theory wherein agents make contracts. We show how agents can modify the behavior of normative systems by means of constitutive rules in the contract changing these systems, and we illustrate how agents use the game theory within contract negotiation in organizations

Knowledge management exploits the new opportunities of sharing knowledge among members of virtual communities in distributed computer networks, and knowledge-management systems are therefore modeled and designed as multiagent systems. In this paper, normative multiagent systems for secure knowledge management based on access-control policies are studied. It is shown how distributed access control is realized by means of local policies of access-control systems for documents of knowledge providers, and by means of global community policies regulating these local policies. Moreover, it is shown how such a virtual community of multiple knowledge providers respects the autonomy of the knowledge providers

The distinction between the notions of permission and authorization is subtle. In the Cambridge Advanced Learner's Dictionary [4] permitting is "to allow something", "to make it possible for someone to do something, or to not prevent something from happening", while authorizing means "to give someone official permission to do something". Law studies argue that the distinction goes beyond the "officiality" of authorization. E.g., the Del Giudice [5]'s dictionary of law argues that adding or removing an authorization does not change the normative status of an agent while adding or removing a permission does. Authorizations change what is obligatory or permitted for agents without adding or removing norms. However, though legal philosophers distinguish permission from authorization, the distinction between the two is ignored in many (agent) theories and systems. How can this apparent paradox be explained?

We are interested in interactive access control to Web services in virtual organizations. We discuss argument games in which the set of credentials requested by the service provider to access a service is established by means of an interaction between a client acting as a proponent and a server acting as an opponent.

In this paper we address the problem of defining roles in organizations like e-trade ones. The methodology we use is to model roles according to the agent metaphor: we attribute to roles mental attitudes, like beliefs, desires and goals, we relate them to the agent's required expertise and responsibilities, and we model role behavior in game theoretic terms. Analogously, the organization is modelled as an agent which acts as a normative system: it imposes obligations to roles and to the agents playing the roles.

We are interested in the design of policies for virtual communities of agents based on the grid infrastructure. In a virtual community agents can play both the role of resource consumers and the role of resource providers, and they remain in control of their resources. We argue that this requirement creates a distinction between two dimensions: global vs local and centralized and decentralized control by means of policies. The providers should be enabled to specify their local policies on their own resources, but their policies should be consistent with the global policies. At the same time, some aspects of the decentralized control should be delegated to specialized providers; this delegation requires a distinction between the authorization to access a resource and a permission to do so.

If a legislator introduces a new norm in a normative system, then rationality prescribes that it ensures that the norm can and will be fulfilled by agents subjected to the norm. Since agents may not follow the law, it associates sanctions with norms. But even with sanction-based obligations, some agents will look for ways to violate the norm while at the same time evading the sanction, for example by making sure that their violation will not be noticed, blocking the sanction, bribing the system, et cetera. Consequently, to reason about the creation of norms, we need a model of norm-evading agents. In [2] we argue that a model of normevading agents can be based on the attribution of mental attitudes to normative systems. In this paper we address the following two questions:1. How can the attribution of mental attitudes to normative systems be used to reason about norm creation?2. How can we formalize norm creation using the attribution of mental attitudes to normative systems?

In this paper we discuss different types of permissions and their roles in deontic logic. We study the distinction between weak and strong permissions in the context of input/output logic, combining the logic with constraints, priorities and hierarchies of normative authorities. In this setting we observe that the notion of prohibition immunity no longer applies, and we introduce a new notion of permission as exception and a new distinction between static and dynamic norms. We show that strong permissions can dynamically change a normative system by adding exceptions to obligations, provide an explicit representation of what is permitted to the subjects of the normative system and allow higher level authorities to limit the changes that lower level authorities can do to the normative system.

Here we study the rational balance between local and global policies in Web based distributed systems. We use a logical framework for multiagent systems to model obligations and permissions composing policies. In particular, a qualitative decision theory allows agents to trade off the decision of respecting a norm against the consequences of not respecting it: the possibility that they are considered violators and thus sanctioned. Global policies refer not to the existence of a local norm but to the fact that it is enforced by the local authority by recognizing and sanctioning violations.

This paper aims at linking the AI notion of action to the notion of LEGAL RELATION. Legal rules concern actions to accomplish or to exclude and states to achieve or to avoid. The body of the rule establishes who and under which conditions must respect the obligation. In this paper, we introduce a definition of obligation and use it as an ontological basis to describe the LEGAL RELATIONS appearing in the A-Hohfeld language.