David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Artificial Intelligence and Law 7 (2-3):289-301 (1999)
Analogy making from examples is a central task in intelligent system behavior. A lot of real world problems involve analogy making and generalization. Research investigates these questions by building computer models of human thinking concepts. These concepts can be divided into high level approaches as used in cognitive science and low level models as used in neural networks. Applications range over the spectrum of recognition, categorization and analogy reasoning. A major part of legal reasoning could be formally interpreted as an analogy making process. Because it is not the same as reasoning in mathematics or the physical sciences, it is necessary to use a method, which incorporates first the ability to specify likelihood and second the opportunity of including known court decisions. We use for modelling the analogy making process in legal reasoning neural networks and fuzzy systems. In the first part of the paper a neural network is described to identify precedents of immaterial damages. The second application presents a fuzzy system for determining the required waiting period after traffic accidents. Both examples demonstrate how to model reasoning in legal applications analogous to recent decisions: first, by learning a system with court decisions, and second, by analyzing, modelling and testing the decision making with a fuzzy system.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
Zsófia Kacsuk (2011). The Mathematics of Patent Claim Analysis. Artificial Intelligence and Law 19 (4):263-289.
Similar books and articles
V. Di Gesù, F. Masulli & Alfredo Petrosino (eds.) (2006). Fuzzy Logic and Applications: 5th International Workshop, Wilf 2003, Naples, Italy, October 9-11, 2003: Revised Selected Papers. [REVIEW] Springer.
Dan Hunter (1999). Out of Their Minds: Legal Theory in Neural Networks. [REVIEW] Artificial Intelligence and Law 7 (2-3):129-151.
István Borgulya (1999). Two Examples of Decision Support in the Law. Artificial Intelligence and Law 7 (2-3):303-321.
Jacky Legrand (1999). Some Guidelines for Fuzzy Sets Application in Legal Reasoning. Artificial Intelligence and Law 7 (2-3):235-257.
Mingqiang Xu, Kaoru Hirota & Hajime Yoshino (1999). A Fuzzy Theoretical Approach to Case-Based Representation and Inference in CISG. Artificial Intelligence and Law 7 (2-3):259-272.
Gualtiero Piccinini (2008). Some Neural Networks Compute, Others Don't. Neural Networks 21 (2-3):311-321.
Henri Prade (1996). New Trends and Open Problems in Fuzzy Logic and Approximate Reasoning. Theoria 11 (3):109-121.
Lothar Philipps & Giovanni Sartor (1999). Introduction: From Legal Theories to Neural Networks and Fuzzy Reasoning. [REVIEW] Artificial Intelligence and Law 7 (2-3):115-128.
Added to index2009-01-28
Total downloads17 ( #108,152 of 1,413,300 )
Recent downloads (6 months)1 ( #154,079 of 1,413,300 )
How can I increase my downloads?