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Abstract  This paper presents an enhanced ontology formalization, combining previous work in Conceptual Structure Theory and Order-Sorted
Logic. Most existing ontology formalisms place greater importance on concept types, but in this paper we focus on relation
types, which are in essence predicates on concept types. We formalize the notion of ‘predicate of predicates’ as meta-relation
type and introduce the new hierarchy of meta-relation types as part of the ontology definition. The new notion of closure
of a relation or meta-relation type is presented as a means to complete that relation or meta-relation type by transferring
extra arguments and properties from other related types. The end result is an expanded ontology, called the closure of the
original ontology, on which automated inference could be more easily performed. Our proposal could be viewed as a novel and
improved ontology formalization within Conceptual Structure Theory and a contribution to knowledge representation and formal
reasoning (e.g., to build a query-answering system for legal knowledge).

Abstract  The research described here explores the idea of using Supreme Court oral arguments as pedagogical examples in first year
classes to help students learn the role of hypothetical reasoning in law. The article presents examples of patterns of reasoning
with hypotheticals in appellate legal argument and in the legal classroom and a process model of hypothetical reasoning that
relates them to work in cognitive science and Artificial Intelligence. The process model describes the relationships between
an advocate’s proposed test for deciding a case or issue, the facts of the hypothetical and of the case to be decided, and
the often conflicting legal principles and policies underlying the issue. The process model of hypothetical reasoning has
been partially implemented in a computerized teaching environment, LARGO (“Legal ARgument Graph Observer”) that helps students
identify, analyze, and reflect on episodes of hypothetical reasoning in oral argument transcripts. Using LARGO, students reconstruct
examples of hypothetical reasoning in the oral arguments by representing them in simple diagrams that focus students on the
proposed test, the hypothetical challenge to the test, and the responses to the challenge. The program analyzes the diagrams
and provides feedback to help students complete the diagrams and reflect on the significance of the hypothetical reasoning
in the argument. The article reports the results of experiments evaluating instruction of first year law students at the University
of Pittsburgh using the LARGO program as applied to Supreme Court personal jurisdiction cases. The learning results so far
have been mixed. Instruction with LARGO has been shown to help law student volunteers with lower LSAT scores learn skills
and knowledge regarding hypothetical reasoning better than a text-based approach, but not when the students were required
to participate. On the other hand, the diagrams students produce with LARGO have been shown to have some diagnostic value,
distinguishing among law students on the basis of LSAT scores, posttest performance, and years in law school. This lends support
to the underlying model of hypothetical argument and suggests using LARGO as a pedagogically diagnostic tool.

Abstract  I shall argue that software agents can be attributed cognitive states, since their behaviour can be best understood by adopting
the intentional stance. These cognitive states are legally relevant when agents are delegated by their users to engage, without
users’ review, in choices based on their the agents’ own knowledge. Consequently, both with regard to torts and to contracts,
legal rules designed for humans can also be applied to software agents, even though the latter do not have rights and duties
of their own. The implications of this approach in different areas of the law are then discussed, in particular with regard
to contracts, torts, and personality.

Abstract  I shall compare two views of legal concepts: as nodes in inferential nets and as categories in an ontology (a conceptual architecture).
Firstly, I shall introduce the inferential approach, consider its implications, and distinguish the mere possession of an
inferentially defined concept from the belief in the concept’s applicability, which also involves the acceptance of the concept’s
constitutive inferences. For making this distinction, the inferential and eliminative analysis of legal concepts proposed
by Alf Ross will be connected to the views on theoretical concepts in science advanced by Frank Ramsey and Rudolf Carnap.
Consequently, the mere comprehension of a legal concept will be distinguished from the application of the concept to a particular
legal system, since application presupposes a doctrinal commitment, namely, the belief that the inferences constituting the
concept hold in that system. Then, I shall consider how concepts can be characterised by defining the corresponding terms
and placing them within an ontology. Finally, I shall argue that there is a tension between the inferential and the ontological
approach, but that both need to be taken into account, to capture the meaning and the cognitive function of legal concepts.

Abstract  We describe PADUA, a protocol designed to support two agents debating a classification by offering arguments based on association
rules mined from individual datasets. We motivate the style of argumentation supported by PADUA, and describe the protocol.
We discuss the strategies and tactics that can be employed by agents participating in a PADUA dialogue. PADUA is applied to
a typical problem in the classification of routine claims for a hypothetical welfare benefit. We particularly address the
problems that arise from the extensive number of misclassified examples typically found in such domains, where the high error
rate is a widely recognised problem. We give examples of the use of PADUA in this domain, and explore in particular the effect
of intermediate predicates. We have also done a large scale evaluation designed to test the effectiveness of using PADUA to
detect misclassified examples, and to provide a comparison with other classification systems.

Abstract  Work on a computer program called SMILE + IBP (SMart Index Learner Plus Issue-Based Prediction) bridges case-based reasoning
and extracting information from texts. The program addresses a technologically challenging task that is also very relevant
from a legal viewpoint: to extract information from textual descriptions of the facts of decided cases and apply that information
to predict the outcomes of new cases. The program attempts to automatically classify textual descriptions of the facts of
legal problems in terms of Factors, a set of classification concepts that capture stereotypical fact patterns that effect
the strength of a legal claim, here trade secret misappropriation. Using these classifications, the program can evaluate and
explain predictions about a problem’s outcome given a database of previously classified cases. This paper provides an extended
example illustrating both functions, prediction by IBP and text classification by SMILE, and reports empirical evaluations
of each. While IBP’s results are quite strong, and SMILE’s much weaker, SMILE + IBP still has some success predicting and
explaining the outcomes of case scenarios input as texts. It marks the first time to our knowledge that a program can reason
automatically about legal case texts.

Abstract  To create a programming environment for contract dispute resolution, we propose an extension of assumption-based argumentation
into modular assumption-based argumentation in which different modules of argumentation representing different knowledge bases
for reasoning about beliefs and facts and for representation and reasoning with the legal doctrines could be built and assembled
together. A distinct novel feature of modular argumentation in compare with other modular logic-based systems like Prolog
is that it allows references to different semantics in the same module at the same time, a feature critically important for
application of argumentation in legal domains like contract dispute resolution where the outcomes of court cases often depend
on whether credulous or skeptical modes of reasoning were applied by the contract parties. We apply the new framework to model
the doctrines of contract breach and mutual mistake.

Abstract  A variety of legal documents are increasingly being made available in electronic format. Automatic Information Search and
Retrieval algorithms play a key role in enabling efficient access to such digitized documents. Although keyword-based search
is the traditional method used for text retrieval, they perform poorly when literal term matching is done for query processing,
due to synonymy and ambivalence of words. To overcome these drawbacks, an ontological framework to enhance the user’s query
for retrieval of truly relevant legal judgments has been proposed in this paper. Ontologies ensure efficient retrieval by
enabling inferences based on domain knowledge, which is gathered during the construction of the knowledge base. Empirical
results demonstrate that ontology-based searches generate significantly better results than traditional search methods.

Abstract  In this paper, we present a particular role for abductive reasoning in law by applying it in the context of an argumentation
scheme for practical reasoning. We present a particular scheme, based on an established scheme for practical reasoning, that
can be used to reason abductively about how an agent might have acted to reach a particular scenario, and the motivations
for doing so. Plausibility here depends on a satisfactory explanation of why this particular agent followed these motivations
in the particular situation. The scheme is given a formal grounding in terms of action-based alternating transition systems
and we illustrate the approach with a running legal example.

Abstract  Considerable attention has been given to the accessibility of legal documents, such as legislation and case law, both in legal
information retrieval (query formulation, search algorithms), in legal information dissemination practice (numerous examples
of on-line access to formal sources of law), and in legal knowledge-based systems (by translating the contents of those documents
to ready-to-use rule and case-based systems). However, within AI & law, it has hardly ever been tried to make the contents
of sources of law, and the relations among them, more accessible to those without a legal education. This article presents
a theory about translating sources of law into information accessible to persons without a legal education. It illustrates
the theory by providing two elaborated examples of such translation ventures. In the first example, formal sources of law
in the domain of exchanging police information are translated into rules of thumb useful for policemen. In the second example,
the goal of providing non-legal professionals with insight into legislative procedures is translated into a framework for
making available sources of law through an integrated legislative calendar. Although the theory itself does not support automating
the several stages described, in this article some hints are given as to what such automation would have to look like.

Abstract  Access to legal information and, in particular, to legal literature is examined for the creation of a search and retrieval
system for Italian legal literature. The design and implementation of services such as integrated access to a wide range of
resources are described, with a particular focus on the importance of exploiting metadata assigned to disparate legal material.
The integration of structured repositories and Web documents is the main purpose of the system: it is constructed on the basis
of a federation system with service provider functions, aiming at creating a centralized index of legal resources. The index
is based on a uniform metadata view created for structured data by means of the OAI approach and for Web documents by a machine
learning approach, which, in this paper, has been assessed as regards document classification. Semantic searching is a major
requirement for legal literature users and a solution based on the exploitation of Dublin Core metadata, as well as the use
of legal ontologies and related terms prepared for accessing indexed articles have been implemented.

Abstract  This paper describes the author’s development and use of a diagramming model in preparing a legal case for which he was responsible.
He combined Wigmorean analysis and object oriented techniques in order to model arguments based on generalisations taken from
the real world and from legal precedent. The paper addresses the modelling issues, but in particular identifies the very real
benefits that affected the way the case was conducted. Those areas in which the model came into its own were principally the
structuring of evidence, the preparation for the cross-examination of witnesses, and ensuring a consistent approach from picking
up the case to making the closing submissions.

Abstract  The paper gives ontologies in the Web Ontology Language (OWL) for Legal Case-based Reasoning (LCBR) systems, giving explicit, formal, and general specifications of a conceptualisation
LCBR. Ontologies for different systems allows comparison and contrast between them. OWL ontologies are standardised, machine-readable
formats that support automated processing with Semantic Web applications. Intermediate concepts, concepts between base-level
concepts and higher level concepts, are central in LCBR. The main issues and their relevance to ontological reasoning and
to LCBR are discussed. Two LCBR systems (AS-CATO, which is based on CATO, and IBP) are analysed in terms of basic and intermediate
concepts. Central components of the OWL ontologies for these systems are presented, pointing out differences and similarities.
The main novelty of the paper is the ontological analysis and representation in OWL of LCBR systems. The paper also emphasises
the important issues concerning the representation and reasoning of intermediate concepts.

Abstract  Increasingly, taxonomies are being developed and used by industry practitioners to facilitate information interoperability
and retrieval. Within a single industrial domain, there exist many taxonomies that are intended for different applications.
Industry specific taxonomies often represent the vocabularies that are commonly used by the practitioners. Their jobs are
multi-faceted, which include checking for code and regulatory compliance. As such, it will be very desirable if industry practitioners
are able to easily locate and browse regulations of interest. In practice, multiple sources of government regulations exist
and they are often organized and classified by the needs of the issuing agencies that enforce them rather than the needs of
the communities that use them. One way to bridge these two distinct needs is to develop methods and tools that enable practitioners
to browse and retrieve government regulations using their own terms and vocabularies, for example, via existing industry taxonomies.
The mapping from a single taxonomy to a single regulation is a trivial keyword matching task. We examine a relatedness analysis
approach for mapping a single taxonomy to multiple regulations. We then present an approach for mapping multiple taxonomies
to a single regulation by measuring the relatedness of concepts. Cosine similarity, Jaccard coefficient and market basket
analysis are used to measure the semantic relatedness between concepts from two different taxonomies. Preliminary evaluations
of the three relatedness analysis measures are performed using examples from the civil engineering and building industry.
These examples illustrate the potential benefits of regulatory usage from the mapping between various taxonomies and regulations.

Abstract  Laws set requirements that force organizations to assess the security and privacy of their IT systems and impose them to implement
minimal precautionary security measures. Several IT solutions (e.g., Privacy Enhancing Technologies, Access Control Infrastructure,
etc.) have been proposed to address security and privacy issues. However, understanding why, and when such solutions have
to be adopted is often unanswered because the answer comes only from a broader perspective, accounting for legal and organizational
issues. Security engineers and legal experts should analyze the business goals of a company and its organizational structure
and derive from there the points where security and privacy problems may arise and which solutions best fit such (legal) problems.
The paper investigates the methodological support for capturing security and privacy requirements of a concrete health care
provider.

Abstract  This paper presents a formal reconstruction of a Dutch civil legal case in Prakken’s formal model of adjudication dialogues.
The object of formalisation is the argumentative speech acts exchanged during the dispute by the adversaries and the judge.
The goal of this formalisation is twofold: to test whether AI & law models of legal dialogues in general, and Prakken’s model
in particular, are suitable for modelling particular legal procedures; and to learn about the process of formalising an actual
legal dispute.

Abstract  This article presents a formal dialogue game for adjudication dialogues. Existing AI & law models of legal dialogues and argumentation-theoretic
models of persuasion are extended with a neutral third party, to give a more realistic account of the adjudicator’s role in
legal procedures. The main feature of the model is a division into an argumentation phase, where the adversaries plea their
case and the adjudicator has a largely mediating role, and a decision phase, where the adjudicator decides the dispute on
the basis of the claims, arguments and evidence put forward in the argumentation phase. The model allows for explicit decisions
on admissibility of evidence and burden of proof by the adjudicator in the argumentation phase. Adjudication is modelled as
putting forward arguments, in particular undercutting and priority arguments, in the decision phase. The model reconciles
logical aspects of burden of proof induced by the defeasible nature of arguments with dialogical aspects of burden of proof
as something that can be allocated by explicit decisions on legal grounds.

Abstract  This paper presents an effort to induce a Bayesian belief network (BBN) from crime data, namely the national crime victimization
survey (NCVS). This BBN defines a joint probability distribution over a set of variables that were employed to record a set
of crime incidents, with particular focus on characteristics of the victim. The goals are to generate a BBN to capture how
characteristics of crime incidents are related to one another, and to make this information available to domain specialists.
The novelty associated with the study reported in this paper lies in the use of a Bayesian network to represent a complex
data set to non-experts in a way that facilitates automated analysis. Validation of the BBN’s ability to approximate the joint
probability distribution over the set of variables entailed in the NCVS data set is accomplished through a variety of sources
including mathematical techniques and human experts for appropriate triangulation. Validation results indicate that the BBN
induced from the NCVS data set is a good joint probability model for the set of attributes in the domain, and accordingly
can serve as an effective query tool.

Abstract  The notions of burden of proof and presumption are central to law, but as noted in McCormick on Evidence, they are also the slipperiest of any of the family of legal terms employed in legal reasoning. However, recent studies of
burden of proof and presumption (Prakken et al. 2005; Prakken and Sartor 2006). Gordon et al. (2007) offer formal models that
can render them into precise tools useful for legal reasoning. In this paper, the various theories and formal models are comparatively
evaluated with the aim of working out a more comprehensive theory that can integrate the components of the argumentation structure
on which they are based. It is shown that the notion of presumption has both a logical component and a dialectical component,
and the new theory of presumption developed in the paper, called the dialogical theory, combines these two components.

Abstract  Infonorma is a multi-agent system that provides its users with recommendations of legal normative instruments they might be
interested in. The Filter agent of Infonorma classifies normative instruments represented as Semantic Web documents into legal
branches and performs content-based similarity analysis. This agent, as well as the entire Infonorma system, was modeled under
the guidelines of MAAEM, a software development methodology for multi-agent application engineering. This article describes
the Infonorma requirements specification, the architectural design solution for those requirements, the detailed design of
the Filter agent and the implementation model of Infonorma, according to the guidelines of the MAAEM methodology.

Abstract  This paper provides a computational framework, based on defeasible logic, to capture some aspects of institutional agency.
Our background is Kanger-Lindahl-Pörn account of organised interaction, which describes this interaction within a multi-modal
logical setting. This work focuses in particular on the notions of counts-as link and on those of attempt and of personal
and direct action to realise states of affairs. We show how standard defeasible logic (DL) can be extended to represent these
concepts: the resulting system preserves some basic properties commonly attributed to them. In addition, the framework enjoys
nice computational properties, as it turns out that the extension of any theory can be computed in time linear to the size
of the theory itself.

Abstract  Intellectual property law tends to be viewed as the only (or most significant) mechanism for achieving policy goals relating
to innovation assets. Yet more creative and effective solutions are often available. When analysed from a transdisciplinary
perspective, relying on the cooperative efforts of researchers from fields other than law, innovation governance is characterized
not simply as the product of legal rules, but as a function of the interaction of legal rules, practices and institutions.
When policy-makers seek to identify conditions under which the creation, use and exchange of innovation assets flourishes,
care should be taken to focus on this combination of factors. This article describes the development of an ontology—a computerized
method of representing knowledge as concepts and relations between concepts—to convey such understanding. Policy makers (and
researchers) are provided with an organized, accessible representation of innovation governance that enriches their understanding
and improves their decision-making.

Abstract  A single global authority is not sufficient to regulate heterogenous agents in multiagent systems based on distributed architectures,
due to idiosyncratic local situations and to the need to regulate new issues as soon as they arise. On the one hand institutions
should be structured as normative systems with a hierarchy of authorities able to cope with the dynamics of local situations,
but on the other hand higher authorities should be able to delimit the autonomy of lower authorities to issue valid norms.
In this paper, we study the interplay of obligations and strong permissions in the context of hierarchies of authorities using
input/output logic, because its explicit norm base facilitates reasoning about norm base maintenance, and it covers a variety of conditional obligations and permissions. We combine the logic with constraints, priorities and hierarchies of authorities. In this setting,
we observe that Makinson and van der Torre’s notion of prohibition immunity for permissions is no longer sufficient, and we
introduce a new notion of permission as exception and a new distinction between static and dynamic norms. We show how strong
permissions can dynamically change an institution 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 power of lower
level authorities to change the normative system.

Abstract  Software agents’ ability to interact within different open systems, designed by different groups, presupposes an agreement
on an unambiguous definition of a set of concepts, used to describe the context of the interaction and the communication language
the agents can use. Agents’ interactions ought to allow for reliable expectations on the possible evolution of the system;
however, in open systems interacting agents may not conform to predefined specifications. A possible solution is to define
interaction environments including a normative component, with suitable rules to regulate the behaviour of agents. To tackle
this problem we propose an application-independent metamodel of artificial institutions that can be used to define open multiagent
systems. In our view an artificial institution is made up by an ontology that models the social context of the interaction,
a set of authorizations to act on the institutional context, a set of linguistic conventions for the performance of institutional
actions and a system of norms that are necessary to constrain the agents’ actions.

Abstract  While the sociality of software agents drives toward the definition of institutions for multi agent systems, their autonomy
requires that such institutions are ruled by appropriate norm mechanisms. Computational institutions represent useful abstractions.
In this paper we show how computational institutions can be built on top of the RoleX infrastructure, a role-based system
with interesting features for our aim. We achieve a twofold goal: on the one hand, we give concreteness to the institution
abstractions; on the other hand, we demonstrate the flexibility of the RoleX infrastructure.

Abstract  In this paper we address the problem of defining social roles in multi-agent systems. Social roles provide the basic structure
of social institutions and organizations. We start from the properties attributed to roles both in the multi-agent systems
and the Object Oriented community, and we use them in an ontological analysis of the notion of social role. We identify three
main properties of social roles. First, they are definitionally dependent on the institution they belong to, i.e. the definition
of a role is given inside the definition of the institution. Second, they attribute powers to the agents playing them, like
creating commitments for the institutions and the other roles. Third, they allow roles to play roles, in the same way as agents
do. Using Input/Output logics, we propose a formalization of roles in multi-agent systems satisfying the three properties
we identified.

Abstract  In order to design and implement electronic institutions that incorporate norms governing the behavior of the participants
of those institutions, some crucial steps should be taken. The first problem is that human norms are (on purpose) specified
on an abstract level. This ensures applicability of the norms over long periods of time in many different circumstances. However,
for an electronic institution to function according to those norms, they should be concrete enough to be able to check them
run time. A second problem is that norms describe which behavior is desirable and permitted, but not how this is achieved
in an institution. In the “real world” regulations often indicate procedures for implementing and enforcing the law. Likewise
we should devise means to annotate the norms with practical aspects such as enforcement mechanisms, sanctions, etc. in order
to get requirements for an institution that will enforce norms (by either constraining behavior within the norms or reacting
to violation of the norms). The choice of which kind of mechanism is chosen is not a normative one, but usually based on criteria
of efficiency and/or feasibility of the mechanism. In this paper we present our view on how to approach these problems and
other related issues to be solved in order to develop e-institutions capable to operate in complex, highly regulated scenarios.

Abstract  The emergence of intelligent software agents that operate autonomously with little or no human intervention has generated
many doctrinal questions at a conceptual level and has challenged the traditional rules of contract especially those relating
to the intention as an essential requirement of any contract conclusion. In this paper, we will try to explore some of these
challenges, and shed light on the conflict between the traditional contract theory and the transactional practice in the case
of using intelligent software agents. We will try further to examine how intelligent software agents differ from other software
applications, and consider then how such differences are legally relevant. This paper, however, is not intended to provide
the final answer to all questions and challenges in this regard, but to identify the main components, and provide perspectives
on how to deal with such issue.

Abstract  Aim of the present paper is to provide a formal characterization of various different notions of responsibility within groups
of agents (Who did that? Who gets the blame? Who is accountable for that? etc.). To pursue this aim, the papers proposes an
organic analysis of organized collective agency by tackling the issues of organizational structure, role enactment, organizational
activities, task-division and task-allocation. The result consists in a semantic framework based on dynamic logic in which
all these concepts can be represented and in which various notions of responsibility find a formalization. The background
motivation of the work consists in those responsibility-related issues which are of particular interest for the theory and
development of multi-agent systems.