A policy describes the conditions under which an action is permitted or forbidden. We show that a fragment of (multi-sorted) first-order logic can be used to represent and reason about policies. Because we use first-order logic, policies have a clear syntax and semantics. We show that further restricting the fragment results in a language that is still quite expressive yet is also tractable. More precisely, questions about entailment, such as `May Alice access the file?', can be answered in time that is a low-order polynomial (indeed, almost linear in some cases), as can questions about the consistency of policy sets. We also give a brief overview of a prototype that we have built whose reasoning engine is based on the logic and whose interface is designed for non-logicians, allowing them to enter both policies and background information, such as `Alice is a student', and to ask questions about the policies.

Deontic logic is the logic that deals with actual as well as ideal behavior of systems. In this paper, we survey a number of applications of deontic logic in computer science that have arisen in the eighties, and give a systematic framework in which these applications can be classified. Many applications move in the direction of programming a computer in deontic logic to make the computer prohibit, permit or obligate people to do something. We discuss conditions under which this possibility is realistic and conditions under which it would be admissible to do so.

Over the years, many different agent programming languages have been proposed. In this paper, we propose a concept called Agent Programs using which, the way an agent should act in various situations can be declaratively specified by the creator of that agent. Agent Programs may be built on top of arbitrary pieces of software code and may be used to specify what an agent is obliged to do, what an agent may do, and what an agent may not do. In this paper, we define several successively more sophisticated and epistemically satisfying declarative semantics for agent programs. We further show that agent programs cleanly extend well understood semantics for logic programs, and thus are clearly linked to existing results on logic programming and nonmonotonic reasoning.

this paper is to show how a collection of specification constructs may be formally defined that supports the former effort. We should stress that we shall not attempt to provide a full and practical specification language that can be used for object-oriented design. We shall have to limit ourselves to concentrate on the definition of our main primitive of specification (formalising the notion of object) together with two well known specification constructs: inheritance and aggregation (complex objects). However, we do not see deep problems in extending our results to other useful constructs such as class/type grouping and parameterisation.

This article is an exercise in computational jurisprudence. It seems clear that the field of AI and Law should draw upon the insights of legal philosophers, whenever possible. But can the computational perspective offer anything in return? I will explore this question by focusing on the concept of OWNERSHIP, which has been debated in the jurisprudential literature for centuries. Although the intellectual currents here flow mostly in one direction — from legal philosophy to AI — I will show that there are also some insights to be gained from a computational analysis of the OWNERSHIP relation. In particular, the article suggests a computational explanation for the emergence of abstract property rights, divorced from concrete material objects.

Abstract. People often need to reason about policy changes before they are adopted. For example, suppose a website manager knows that users want to enter her site without going through the welcome page. To decide whether or not to permit this, the wise manager will consider the consequences of modifying the policies (e.g., would this allow users to bypass advertisements and legal notices?). Similiarly, people often need to compare policy sets. For example, consider a person who wants to buy health insurance. Before choosing a provider, the customer will want to compare the different policies. In other words, the customer wants to reason about the effect of choosing one policy set over another. We introduce a logic, based on propositional dynamic logic, in which these tasks can be done. We give a sound and complete axiomatization for our logic, and also show that it is decidable. More precisely, the satisfiability problem is decidable in nondeterministic exponential time. 1

Abstract Applications of deontic logic in areas such as intelligent legal information systems require the ability to represent at least two different notions of permission, one of which, "free choice permission, " cannot be adequately represented in standard modal logics. We define a logic which handles this modality by using ideas from dynamic logic. The logic is also able to expresses a different notion of permission corresponding to a lack of prohibition. The main result is the completeness of an axiomatization of the logic.

Most work in artificial intelligence and law has concentrated on modelling the type of reasoning done by trial lawyers. In fact, most lawyers' work involves planning -- for example, wills and trusts, real estate deals, and business mergers and acquisitions. Certain planning issues, such as the use of underspecified, or "open-textured" rules, are illustrated especially clearly in this domain. In this thesis, I set forth the characteristic features of planning in law, place it in the context of past artificial intelligence work in both law and planning, and describe CHIRON, a system that I have developed implementing my theory of open-textured planning in the domain of personal income tax law.

. Updates are a crucial component of any database programming language. Even the simplest database transactions, such as withdrawal from a bank account, require updates. Unfortunately, updates are not accounted for by the classical Horn semantics of logic programs and deductive databases, which limits their usefulness in real-world applications. As a short-term practical solution, logic programming languages have resorted to handling updates using ad hoc operators without a logical semantics. A great many works have been dedicated to developing logical theories in which the state of the underlying database can evolve with time. Many of these theories were developed with specific applications in mind, such as reasoning about actions, database transactions, program verification, etc. As a result, the different approaches have different strengths and weaknesses. In this survey, we review a number of these works, discuss their application domains, and highlight their strong and weak points...

In this paper we explore the trend towards the production of "ontologies" as part of the development of knowledge based systems, both in general AI and in the legal domain in particular. We discuss four examples of this kind of work in the legal domain and identify areas on which future work might be directed. Introduction Since their introduction, knowledge based and expert systems have attracted a mixed reaction, mingling excitement at their potential with dissatisfaction with their various limitations. This has been true both in general AI, and in the legal field. Much work has therefore concentrated on understanding the limitations, and developing methods for building the systems which can mitigate the limitations. The overall trend has been away from seeing the process as one of encoding heuristics derived from an expert, towards modelling the domain on which the expertise operates. Further it has become recognised that modelling requires as a precondition that the domain be con...