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Topic: Case based reasoning

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	Info and facts on 'Case-based reasoning' (Site not responding. Last check: 2007-11-06)
		Or, more radically, that all reasoning is based on past cases experienced or accepted by the being actively exercising choice -- prototype theory -- most deeply explored in human cognitive science (The field of science concerned with cognition; includes parts of cognitive psychology and linguistics and computer science and cognitive neuroscience and philosophy of mind).
		CBR therefore tends to be a good approach for rich, complex domains in which there are myriad ways to generalize a case.
		CBR traces its roots to the work of Roger Schank (additional info and facts about Roger Schank) and his students at Yale University in the early 1980s.
	www.absoluteastronomy.com /encyclopedia/c/ca/case-based_reasoning.htm (1222 words)

	Encyclopedia: Case based reasoning
		Cases (precedents) are here not used to produce a single answer, but to interpret a situation in court, and to produce and assess arguments for both parties.
		Cases may be indexed by a prefixed or open vocabulary, and within a flat or hierarchical index structure.
		The case may still be learned, and be available in the case base in the intermediate period, but it has to be marked as a non-evaluated case.
	www.nationmaster.com /encyclopedia/Case_based-reasoning (1250 words)

	Case-based Reasoning
		This type of reasoning is based on the premise that human beings learn and solve complex problems by using analogical or experiential reasoning.
		Case-based knowledge is evident in precedence based reasoning (such as in tax law or accounting) and is useful when little evidence is available or the information is incomplete.
		If no reasonably appropriate prior case is found, then the current case and its human created solution can be added to the case base thus allowing the system to learn.
	www.geocities.com /expertsystems_2000/casebased.htm (473 words)

	AICom paper
		CBR methods may be purely self-contained and automatic, or they may interact heavily with the user for support and guidance of its choices.
		Finding a case in the case base that matches an input description is done by combining the input features of a problem case into a pointer to the case or category that shares most of the features.
		Cases that match all input features are, of course, good candidates for matching, but - depending on the strategy - cases that match a given fraction of the problem features (input or inferred) may also be retrieved.
	www.iiia.csic.es /People/enric/AICom.html (12228 words)

	[No title]
		Historically and philosophically, CBR exists as a reaction to rule-based reasoning: In CBR, the emphasis is on the case, not the rule.
		CBR seeks to determine a "source case" relevant to a given "target case." All CBR systems separate their reasoning into two stages: (1) finding the appropriate source case (retrieving); and (2) determining the appropriate conclusions in the target case (revising/reusing).
		He refers to cases as "memories," retrieval of cases as "remindings," and representation of cases as "memory organization." Systems that owe their origin to this school of thought are considerable in scope and ability.
	www.cs.wustl.edu /~loui/mitcs (1432 words)

	Case-Based Reasoning (Site not responding. Last check: 2007-11-06)
		Case-based reasoning builds on the idea that human expertise is not composed of formal structures like rules, but of experience: a human expert reasons by relating a new problem to previous ones.Case-based reasoning now amounts to reasoning by comparing a new problem with a set of stored previous problems with their solution.
		A major problem in case-based reasoning however, resides in the retrieval of cases that are sufficiently similar to a new problem at hand.
		Based on the specific measure employed, the system associates a numerical value with each case indicating the similarity between this case and the problem under consideration.
	www.tenback.org /Robert/cbr.html (490 words)

	Case based reasoning (Site not responding. Last check: 2007-11-06)
		Case-based reasoning (CBR) is an intelligent-systems method that enables information managers to increase efficiency and reduce cost by substantially automating processes such as diagnosis, scheduling and design.
		A case-based reasoner works by matching new problems to "cases" from a historical database and then adapting successful solutions from the past to current situations.
		A collection of cases is called a case base and makes it possible to support for instance decision support for a specific part of a domain.
	www.rossena.nl /caseb.htm (256 words)

	Case-Based Reasoning: A Review (published in The Knowledge Engineering Review, Vol.9 No.4, 1994) (Site not responding. Last check: 2007-11-06)
		Case storage is an important aspect in designing efficient CBR systems in that, it should reflect the conceptual view of what is represented in the case and take into account the indices that characterise the case.
		The goal of CBR systems is thus to be reminded of similar cases when faced with a new problem and to retrieve those cases in order to help the user solve the new problem in a fashion similar to the way it was solved for a closely matching situation.
		Magaldi, R.V. CBR for Troubleshooting Aircraft on the Flightline.
	www.ai-cbr.org /classroom/cbr-review.html (14313 words)

	Case-Based Reasoning
		Case-based Reasoning (CBR) is based on the intuition that new problems are often similar to previously encountered problems and, therefore, that past solutions may be of use in the current situation."
		Instead of implying that legal reasoning is primarily a process of deduction or a process of analogising the theory of law as discourse requires a richer view of the process of legal reasoning."
		CBR research projects in areas such as design, estimating, planning, decision support, finance, and legal reasoning.
	www.aaai.org /AITopics/html/casebased.html (1609 words)

	Case-Based Reasoning
		Case-based reasoning (CBR) is the enterprise of solving new problems by analogy with old ones.
		Problems and their solutions are stored as cases, and to solve a new problem, a CBR system retrieves a case of a similar problem, and adapts its solution to solve the new problem.
		Cases can suggest solutions even to ill-defined problems in weak-theory domains for which there may be no adequate set of rules or hard-wired algorithms.
	www.geocities.com /andrewbroad/cs/cbr (239 words)

	Case based reasoning - Computing Reference - eLook.org
		There are many situations where experts are not happy to be questioned about their knowledge by people who want to write the knowledge in rules, for use in expert systems.
		In most of these situations, the natural way for an expert to describe his or her knowledge is through examples, stories or cases (which are all basically the same thing).
		Some key research areas are efficient indexing, how to define "similarity" between cases and how to use temporal information.
	www.elook.org /computing/case-based-reasoning.htm (159 words)

	CASE-BASED REASONING (Site not responding. Last check: 2007-11-06)
		The course is aiming to provide the students with the background knowledge in the field of case-based reasoning - a new paradigm for combining problem-solving and learning.
		The different aspects of case-based reasoning process will be illustrated by the examples of CBR systems that use past experience to solve problems in different problem domains.
		Introduction to Case-Based Reasoning - case studies in case-based reasoning systems, general model of case-based reasoning process.
	www-it.fmi.uni-sofia.bg /cbreng.html (410 words)

	Case-Based Reasoning (CBR) at Indiana University (Site not responding. Last check: 2007-11-06)
		Our projects focus especially on issues in case-base maintenance, the use of introspective reasoning to refine indexing and adaptation, integration of CBR with other information tools in a larger task context, case-based knowledge management, and case-based components for scientific computing.
		The CBR group at Indiana University is directed by David Leake.
		Electronic reprints of selected publications by the Indiana University CBR group are available on the Web.
	www.cs.indiana.edu /hyplan/leake/cbr/overview.html (194 words)

	AI Publications (Site not responding. Last check: 2007-11-06)
		The tutorial in chapter 2 of this volume presents a thorough discussion of key CBR principles and issues and how to develop CBR systems.
		Kolodner's textbook presents an extensive examination of CBR issues and survey of American CBR research.
		These two books present distillations of a number of influential dissertations on case-based reasoning research, in addition to micro versions of CBR programs developed to facilitate experimentation.
	www.aaai.org /Resources/CB-Reasoning/cbr-resources.html (471 words)

	Case-Based Reasoning
		We are, in essence, creating theories about the minute details in the world around us, trying to create a theory of dry cleaners that will help us to select the right one, or a theory of state government, or the behavior of our friends that will allow us to better function in the world.
		We are constantly accumulating cases and comparing those cases to the cases we have already accumulated in a effort to understand the next case that will appear.
		Or, to put this another way, being educated means, in its deepest sense, having access to a wealth of cases from which to generalize.
	www.engines4ed.org /hyperbook/nodes/NODE-23-pg.html (550 words)

	Case Based Reasoning (Site not responding. Last check: 2007-11-06)
		Over the last eight years, we have been working on the problem of case-based reasoning (CBR) for medical diagnosis.
		Through a succession of research projects, we developed a system that used physiologic causes to match findings in cases, evaluated the system on 240 cases, and developed a system that divides cases and memory based on the diagnostic units in the case.
		Still, it is clear that CBR has not reached its potential to effectively handle the case material and work in concert with a model-based program.
	groups.csail.mit.edu /medg/projects/cbr.html (148 words)

	CBR (IICAI-05) (Site not responding. Last check: 2007-11-06)
		A Special Session on Case-Based Reasoning will be held during the 2
		The session focuses on all areas of case-based reasoning and its applications.
		Authors are encouraged to submit the papers for the session.
	www.iiconference.org /cbr.html (232 words)

	CBRII (Site not responding. Last check: 2007-11-06)
		Case-Based Reasoning (CBR) can be used both as a technology and a methodology to develop Artificial Intelligence systems.
		The special track on CBR is intended to gather AI researchers from the CBR community and who have also participated in past FLAIRS conferences, as well as welcoming new ones by providing a specific forum for CBR.
		Although not restricting to a specific topic, we strongly encourage submissions addressing evaluation of CBR systems, particularly evaluation of methods for case base maintenance, textual CBR, and case-based retrieval.
	www.aic.nrl.navy.mil /~weber/flairs.html (296 words)

	David W. Aha: CBR Resources (Site not responding. Last check: 2007-11-06)
		Case-Based Reasoning: A Categorised Bibliography (Marir & Watson)
		Reasoning with Complex Cases (Friedrich Gebhardt, Angi Voß, Wolfgang Gräther, and Barbara Schmidt-Belz)
		CBR Tutorial at the 1996 British Computer Society Expert Systems Conference (in PowerPoint)
	home.earthlink.net /~dwaha/research/case-based-reasoning.html (713 words)

	CBRII
		We invite submissions for the special track on Case-based Reasoning at the 16th International FLAIRS 2003 conference.
		This is the third installment of the special track on CBR at FLAIRS.
		Selected papers will be invited to submit a revised copy of their paper to a special issue of The
	www.cse.lehigh.edu /~munoz/flairs/flairs.html (291 words)

	The Case-Based Reasoning Group (Site not responding. Last check: 2007-11-06)
		Research in Professor Edwina Rissland's CBR Group deals with case-based reasoning (CBR), AI and Legal Reasoning, CBR and machine learning, CBR and information retrieval, and CBR and scheduling.
		CBR-IR - a case-based information retrieval system that uses CBR-determined relevant cases to generate queries that are submitted to INQUERY.
		BROADWAY - a CBR system whose retrieval is relative to the type of case.
	www.cs.umass.edu /~cbr (210 words)

	FLAIRS-2004 : CBR special track (Site not responding. Last check: 2007-11-06)
		Following successful special tracks on Case-Based Reasoning at FLAIRS over the past three years, we are inviting papers for the Fourth Special Track on CBR at the 17th International FLAIRS Conference.
		This forum is intended to gather AI researchers and practitioners with an interest in CBR to present and discuss developments in CBR theory and application.
		Authors may be invited to submit a revised copy of their paper to a special issue of the International Journal of Artificial Intelligence Tools (IJAIT).
	www.cs.indiana.edu /~raja/flairs04 (408 words)

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