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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Artificial intelligence and law 4 (1996), S. 157-161 
    ISSN: 1572-8382
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Type of Medium: Electronic Resource
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  • 2
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    Artificial intelligence and law 4 (1996), S. 133-156 
    ISSN: 1572-8382
    Keywords: artificial intelligence ; knowledge engineering ; legal expert systems ; building contracts ; breach of contract
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract Although Berman and Hafner [Berman 1989, pp. 928–938] presented the possibility to adapt the model of reasoning of development of an expert system for medical diagnosis to the reasoning of a judge when he/she sentences criminals does not resemble the reasoning found in the decisions of physicians, mathematicians or statisticians. When a lawyer reasons, he/she not only looks for the solution of a case; he/she simultaneously looks for the bases on which his/her reasoning can rest [Galindo 1992, pp. 363–367]. That is to say, he/she not only needs to find the solution but moreover he/she has to find the references (laws, jurisprudence and bibliography) that allow him/her to argue the solution. In many cases, computer solutions to these reasoning processes have been made in a separated way: the solution to the cases using expert systems, and the search of documentation using information retrieval systems. This paper presents the ARPO-2 prototype, a solution integrating the two aspects of legal reasoning: an expert system which is able to simultaneously find the solution to a problem and to give the necessary references so that the lawyer argues the solution. The subject on which the prototype solves problems is the breach of building contracts. In this paper, we describe the process of development of an expert system for solving, justification and documentation of ‘breach of contracts’, giving details on the way how the objects that intervene in the case were defined as well as on the reasoning followed.
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  • 3
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    Artificial intelligence and law 4 (1996), S. 163-197 
    ISSN: 1572-8382
    Keywords: argumentation ; legal reasoning ; burden of proof
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract We present a computational model of dialectical argumentation that could serve as a basis for legal reasoning. The legal domain is an instance of a domain in which knowledge is incomplete, uncertain, and inconsistent. Argumentation is well suited for reasoning in such weak theory domains. We model argument both as information structure, i.e., argument units connecting claims with supporting data, and as dialectical process, i.e., an alternating series of moves by opposing sides. Our model includes burden of proof as a key element, indicating what level of support must be achieved by one side to win the argument. Burden of proof acts as move filter, turntaking mechanism, and termination criterion, eventually determining the winner of an argument. Our model has been implemented in a computer program. We demonstrate the model by considering program output for two examples previously discussed in the artificial intelligence and legal reasoning literature.
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  • 4
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    Artificial intelligence and law 4 (1996), S. 275-296 
    ISSN: 1572-8382
    Keywords: argumentation ; default reasoning ; priority
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract In this paper we explore the thesis that the role of argumentation in practical reasoning in general and legal reasoning in particular is to justify the use of defeasible rules to derive a conclusion in preference to the use of other defeasible rules to derive a conflicting conclusion. The defeasibility of rules is expressed by means of non-provability claims as additional conditions of the rules. We outline an abstract approach to defeasible reasoning and argumentation which includes many existing formalisms, including default logic, extended logic programming, non-monotonic modal logic and auto-epistemic logic, as special cases. We show, in particular, that the ‘admissibility’ semantics for all these formalisms has a natural argumentation-theoretic interpretation and proof procedure, which seem to correspond well with informal argumentation. In the admissibility semantics there is only one way for one argument to attack another, namely by undermining one of its non-provability claims. In this paper, we show how other kinds of attack between arguments, specifically how rebuttal and priority attacks, can be reduced to the undermining of non-provability claims.
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  • 5
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    Artificial intelligence and law 4 (1996), S. 199-273 
    ISSN: 1572-8382
    Keywords: legal reasoning ; reasoning with principles and rules ; non-monotonic logic
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract This paper describes a model of legal reasoning and a logic for reasoning with rules, principles and goals that is especially suited to this model of legal reasoning. The paper consists of three parts. The first part describes a model of legal reasoning based on a two-layered view of the law. The first layer consists of principles and goals that express fundamental ideas of a legal system. The second layer contains legal rules which in a sense summarise the outcome of the interaction of the principles and goals for a number of case types. Both principles, goals and rules can be used in legal arguments, but their logical roles are different. One characteristic of the model of legal reasoning described in the first part of the paper is that it takes these logical differences into account. Another characteristic is that it pays serious attention to the phenomena of reasoning about the validity and acceptance of rules, respectively principles and goals, and about the application of legal rules, and the implications of these arguments for the use of rules, principles and goals in deriving legal conclusions for concrete cases. The second part of the paper first describes a logic (Reason-Based Logic) that is especially suited to deal with legal arguments as described in terms of the previously discussed model. The facilities of the logic are illustrated by means of examples that correspond to the several aspects of the model. The third part of the paper deals with a number of logico-philosophical reflections on Reason-Based Logic. The occasion is also used to compare these presuppositions with theories of defeasible reasoning based on the comparison of arguments.
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  • 6
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    Artificial intelligence and law 4 (1996), S. 297-329 
    ISSN: 1572-8382
    Keywords: coherence ; defeasibility ; nonmonotonic logic ; principles ; weighing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract The main stream of legal theory tends to incorporate unwritten principles into the law. Weighing of principles plays a great role in legal argumentation, inter alia in statutory interpretation. A weighing and balancing of principles and other prima facie reasons is a jump. The inference is not conclusive. To deal with defeasibility and weighing, a jurist needs both the belief-revision logic and the nonmonotonic logic. The systems of nonmonotonic logic included in the present volume provide logical tools enabling one to speak precisely about various kinds of “rules about rules”, dealing with such things as applicability of rules, what is assumed by rules, priority between rules and the burden of proof. Nonmonotonic logic is an example of an extension of the domain of logic. But the more far-reaching the extension is, the greater problems it meets. It seems impossible to make logical reconstruction of the totality of legal argumentation. The lawyers' search for reasons has no obvious end point. Ideally, the search for reasons may end when one arrives at a coherent totality of knowledge. In other words, coherence is the termination condition of reasoning. Both scientific knowledge and knowledge of legal and moral norms progresses by trial and error, and that one must resort to a certain convention to define what “error” means. The main difference is, however, that conventions of science are much more precise than those of legal scholarship. Consequently, determination of “error” in legal science is often holistic and circular. The reasons determining that a legal theory is “erroneous” are not more certain than the contested theory itself. A strict and formal logical analysis cannot give us the full grasp of legal rationality. A weaker logical theory, allowing for nonmonotonic steps, comes closer, at the expense of an inevitable loss of computational efficiency. Coherentist epistemology grasps even more of this rationality, at the expense of a loss of preciseness.
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  • 7
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    Artificial intelligence and law 4 (1996), S. 331-368 
    ISSN: 1572-8382
    Keywords: argumentation ; defeasibility ; dialectics ; rule conflicts ; logic programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is of a logic-programming-like nature, has both weak and explicit negation, and conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that these priorities are not fixed, but are themselves defeasibly derived as conclusions within the system. Thus debates on the choice between conflicting arguments can also be modelled. The proof theory of the system is stated in dialectical style, where a proof takes the form of a dialogue between a proponent and an opponent of an argument. An argument is shown to be justified if the proponent can make the opponent run out of moves in whatever way the opponent attacks. Despite this dialectical form, the system reflects a ‘declarative’, or ‘relational’ approach to modelling legal argument. A basic assumption of this paper is that this approach complements two other lines of research in AI and Law, investigations of precedent-based reasoning and the development of ‘procedural’, or ‘dialectical’ models of legal argument.
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  • 8
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    Artificial intelligence and law 4 (1996), S. 1-71 
    ISSN: 1572-8382
    Keywords: legal argument ; heuristic search ; best-first search ; evaluation function ; bankruptcy law ; “good faith” ; information retrieval ; information harvesting ; case-domain graph ; argument pieces ; argument dimensions ; argument factors ; neighbor methods
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract The BankXX system models the process of perusing and gathering information for argument as a heuristic best-first search for relevant cases, theories, and other domain-specific information. As BankXX searches its heterogeneous and highly interconnected network of domain knowledge, information is incrementally analyzed and amalgamated into a dozen desirable ingredients for argument (called argument pieces), such as citations to cases, applications of legal theories, and references to prototypical factual scenarios. At the conclusion of the search, BankXX outputs the set of argument pieces filled with harvested material relevant to the input problem situation. This research explores the appropriateness of the search paradigm as a framework for harvesting and mining information needed to make legal arguments. In this article, we describe how legal research fits the heuristic search framework and detail how this model is used in BankXX. We describe the BankXX program with emphasis on its representation of legal knowledge and legal argument. We describe the heuristic search mechanism and evaluation functions that drive the program. We give an extended example of the processing of BankXX on the facts of an actual legal case in BankXX's application domain — the good faith question of Chapter 13 personal bankruptcy law. We discuss closely related research on legal knowledge representation and retrieval and the use of search for case retrieval or tasks related to argument creation. Finally we review what we believe are the contributions of this research to the understanding of the diverse disciplines it addresses.
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  • 9
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    Artificial intelligence and law 4 (1996), S. 73-76 
    ISSN: 1572-8382
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
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  • 10
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    Artificial intelligence and law 4 (1996), S. 77-111 
    ISSN: 1572-8382
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
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