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This paper describes one way in which a precise reason model of precedent could be developed, based on the general idea that courts are constrained to reach a decision that is consistent with the assessment of the balance of reasons made in relevant earlier decisions. The account provided here has the additional advantage of showing how this reason model can be reconciled with the traditional idea that precedential constraint involves rules, as long as these rules are taken to be defeasible. (...) |
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This paper shows how two models of precedential constraint can be broadened to include legal information represented through dimensions. I begin by describing a standard representation of legal cases based on boolean factors alone, and then reviewing two models of constraint developed within this standard setting. The first is the “result model”, supporting only a fortiori reasoning. The second is the “reason model”, supporting a richer notion of constraint, since it allows the reasons behind a court’s decisions to be taken (...) |
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This paper gives an account of dimensions in the reason model found in Horty : 1–33, 2011), Horty and Bench-Capon and Rigoni :133–160, 2015. doi: 10.1007/s10506-015-9166-x). The account is constructed with the purpose of rectifying problems with the approach to incorporating dimensions in Horty, namely, the problems arising from the collapse of the distinction between the reason model and the result model on that approach. Examination of the newly constructed theory revealed that the importance of dimensions in the reason model (...) |
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In this short note, we discuss several aspectsof “dimensions” and the related constructof “factors”. We concentrate on those aspectsthat are relevant to articles in this specialissue, especially those dealing with the analysisof the wild animal cases discussed inBerman and Hafner's 1993 ICAIL article. We reviewthe basic ideas about dimensions,as used in HYPO, and point out differences withfactors, as used in subsequent systemslike CATO. Our goal is to correct certainmisconceptions that have arisen over the years. |
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Law and legal reasoning are a natural target for artificial intelligence systems. Like medical diagnosis and other tasks for expert systems, legal analysis is a matter of interpreting data in terms of higher-level concepts. But in law the data are more like those for a system aimed at understanding natural language: they tell a story about human events that may lead to a lawsuit. Statements of the law, too, are written in natural language and legal arguments are often arguments about (...) |
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The doctrine of precedent, as it has evolved within the common law, has at its heart a form of reasoning—broadly speaking, alogic—according to which the decisions of earlier courts in particular cases somehow generalize to constrain the decisions of later courts facing different cases, while still allowing these later courts a degree of freedom in responding to fresh circumstances. Although the techniques for arguing on the basis of precedent are taught early on in law schools, mastered with relative ease, and (...) |
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In this short note, we discuss several aspectsof dimensions and the related constructof factors. We concentrate on those aspectsthat are relevant to articles in this specialissue, especially those dealing with the analysisof the wild animal cases discussed inBerman and Hafner's 1993 ICAIL article. We reviewthe basic ideas about dimensions,as used in HYPO, and point out differences withfactors, as used in subsequent systemslike CATO. Our goal is to correct certainmisconceptions that have arisen over the years. |
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In previous work, I showed how the “reason model” of precedential constraint could naturally be generalized from the standard setting in which it was first developed to a richer setting in which dimensional information is represented as well. Surprisingly, it then turned out that, in this new dimensional setting, the reason model of constraint collapsed into the “result model,” which supports only a fortiori reasoning. The purpose of this note is to suggest a modification of the reason model of constraint (...) |
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