Ashley, Kevin D. and Rissland, Edwina L. 1987. Compare and contrast, a test of expertise. In Proceedings of the Sixth National Conference on Artificial Intelligence, Seattle, Washington. 273--278.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....A large part of a lawyer s training involves learning to make arguments for and against the application of some statutory predicate, 4 and for and against the similarity of a previous case to the current one. This is one of the key legal skills, particularly in the Anglo American legal system [Ashley and Rissland, 1987, Levi, 1949, Llewellyn, 1930] Anglo American law requires the presentation of competing examples. Levi, 1949, p. 5] Although one result may be more likely than another, it is generally possible to make these arguments in both directions. Ideally, experts in other domains would reach the ....

Ashley, Kevin D. and Rissland, Edwina L. 1987. Compare and contrast, a test of expertise. In Proceedings of the Sixth National Conference on Artificial Intelligence, Seattle, Washington. 273--278.

....in problem domains that can be adequately described using discrete, symbolic representations. For example, CHEF uses case based planning to create recipes ( 22] AQUA uses case based explanation to understand newspaper stories ( 45] HYPO uses case based interpretation for legal argumentation ([5]) MEDIATOR uses case based problem solving for dispute resolution ( 26] and PRODIGY uses case based reasoning in the form of derivational analogy for high level robot planning ( 60] 1 E mail: ashwin cc.gatech.edu. URL: http: www.cc.gatech.edu faculty ashwin 2 E mail: ....

K. Ashley and E. Rissland, Compare and Contrast, A Test of Expertise, in: Proceedings of the Sixth National Conference on Artificial Intelligence (Morgan Kaufmann, Los Altos, CA, 1987) 273--284.

....the similarity of prior cases stored in their memories. Likewise, in legal domains, input cases are routinely described in legal briefs that include all relevant features of the situation under consideration; they provide all the information that needs to be considered by CBR systems such as HYPO (Ashley Rissland, 1987) and GREBE (Branting Porter, 1991) as those systems identify similar cases. In such domains, for which input cases are guaranteed to include sufficient relevant features, traditional similarity assessment comparison of the new case s features with features of a stored case is appropriate. ....

.... circumstances affect similarity assessment: Previous CBR research has proposed models of similarity assessment that are dynamic with respect to changing system goals for applying retrieved cases; in those models current goals determine which features to consider important in a given situation (Ashley Rissland, 1987; Kolodner, 1989; Leake, 1991) The constructive similarity assessment process is dynamic in a different way: It elaborates new situations according to the current contents of memory specific cases, general background knowledge and specific beliefs and dynamically alters how it will understand ....

Ashley, K. & Rissland, E. (1987). Compare and contrast, a test of expertise. In Proceedings of the Sixth Annual National Conference on Artificial Intelligence, pp. 273--284 Palo Alto. AAAI, Morgan Kaufmann, Inc.

....that may only be soluble after significant effort. The Use of CBR in Weak Theory Domains Highly deductive KBS techniques, such as theorem proving or explanation based reasoning, depend heavily on the possession of a complete causal model of the problem domain. In weak theory domains, such as law [6, 16, 7, 125] the causal model will, at best, be incomplete. In such domains the use of precedent cases (i.e CBR) may be the most suitable form of reasoning. Ease of Construction A major problem generally associated with the construction of a KBS is the so called knowledge acquisition bottleneck . This ....

Kevin D Ashley and Edwina L Rissland. Compare and Contrast, A Test Of Expertise. In AAAI-87: Proceedings of the Sixth National Conference on Artificial Intelligence., pages pp273--278. Morgan Kaufmann Publishers, July 1987.

....prior cases to suggest solutions that might apply to new circumstances. 3. 1 Case based interpretation In interpretive CBR, the reasoner s goal is to form a judgment about or classification of a new situation, by comparing and contrasting it with cases that have already been classified (e.g. Ashley Rissland, 1987). For example, interpretive CBR plays a fundamental role in interpreting legal concepts and applying laws in the American legal system (e.g. Ashley, 1990; Bain, 1986; Branting, 1991; Cuthill, 1992; Sanders, 1994) A tax lawyer arguing that his or her client should receive a home office ....

Ashley, K., and Rissland, E. 1987. Compare and contrast, a test of expertise. In Proceedings of the Sixth Annual National Conference on Artificial Intelligence, 273--284. Menlo Park, CA: Morgan Kaufmann.

....al. 1985; CHEF: Hammond, 1989) 2 However, there are many complex problem situations that would seem 1 We use the term model in the sense of Weiss (Casnet; 1978) or Nii et al. Sonar interpretation; 1982) rather than in the qualitative reasoning sense that the term often now connotes in AI. 2 Ashley and Rissland (HYPO; 1987) do not attempt to select the single most closely matching case but rather to retrieve all cases which match (or nearly match) the current case on any relevant underlying dimensions; Redmond (CELIA; 1990) does not in principle, but does in published examples; Hinrichs and Kolodner (1991) retrieves ....

Ashley, K.D. and Rissland E.L. (1987). Compare and Contrast, a test of expertise.

....of experience may exhibit widely divergent levels of skill, sometimes reaching 1 This paper focuses on case based reasoning for problem solving. We will not discuss another important side of case based research, case based reasoning for interpretation and classification (e.g. Ashley (1990) Ashley Rissland (1987), Bareiss (1989) Branting Porter (1991) plateaus of performance that fall short of mastery of their tasks (e.g. Bereiter Scardamalia (1993) Ericsson Smith (1991) Lesgold, Rubinson, Feltovitch, Glaser, Klopfer, Wang (1988) Thus expertise depends not only on experiences, but also ....

....in conjunction with other reasoning methods. For example, in domains for which a complete domain theory is available and for which optimal solutions are essential, reasoning from first principles may be appropriate. The integration of reasoning from general knowledge and from specific cases (e.g. Ashley Rissland (1987), Branting Porter (1991) Hinrichs (1992) Redmond (1992) can also play an important role in the reasoning process. For example, Lancaster and Kolodner (1988) show that expert mechanics use both remindings of specific problems and reasoning from abstract domain models when they diagnose ....

Ashley, K. & Rissland, E. (1987). Compare and contrast, a test of expertise. In Proceedings of the Sixth Annual National Conference on Artificial Intelligence, pp. 273--284 Palo Alto. AAAI, Morgan Kaufmann, Inc.

....In other words, we often know more about features than just the minimal fact that they are influential in some way. It is this knowledge we aim to capture in our formalism. Finally, a representation of weak background knowledge has been proposed by Ashley and Rissland in the domain of law [Ashley and Rissland, 1987], Ashley and Rissland, 1988] Their system Hypo includes a representation of the relative (rather than absolute) influences of different features or dimensions on a hypothesis (e.g. the presence of feature X constitutes increased evidence for conclusion Y) Thus knowledge which is too weak alone ....

Kevin D. Ashley and Edwina L. Rissland. Compare and contrast, a test of expertise. In AAAI-87, pages 273--278, 1987.

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Ashley, Kevin D. & Rissland, Edwina L. (1988a). Compare and Contrast, A Test of Expertise. Proceedings of a Workshop on Case-Based Reasoning, 31-36.

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