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 Memory-Based Learning


The 1996 Simon Newcomb Award

AI Magazine

Simon Newcomb was a distinguished astronomer and computer who "proved" that heavier- than-air flight was impossible. His proofs are ingenious, cleverly argued, quite convincing to many of his contemporaries, and utterly wrong. The Simon Newcomb Award is given annually for the silliest published argument attacking AI. Our subject may be unique in the virulence and frequency with which it is attacked, both in the popular media and among the cultured intelligentsia. Recent articles have argued that the very idea of AI reflects a cancer in the heart of our culture and have proven (yet again) that it is impossible. While many of these attacks are cited widely, most of them are ridiculous to anyone with an appropriate technical education.


Case-Based Reasoning

AI Magazine

The 1994 Workshop on Case-Based Reasoning (CBR) focused on the evaluation of CBR theories, models, systems, and system components. The CBR community addressed the evaluation of theories and implemented systems, with the consensus that a balance between novel innovations and evaluations could maximize progress.


Case-Based Reasoning

AI Magazine

The 1994 Workshop on Case-Based Reasoning (CBR) focused on the evaluation of CBR theories, models, systems, and system components. The CBR community addressed the evaluation of theories and implemented systems, with the consensus that a balance between novel innovations and evaluations could maximize progress.



Review of Case-Based Reasoning

AI Magazine

Sometimes a section will system shells, have made their way anew, and the reader must recall the introduce a list of points to be covered, into the marketplace.


Applying Case-Based Reasoning to Manufacturing

AI Magazine

CLAVIER is a case-based reasoning (CBR) system that assists in determining efficient loads of composite material parts to be cured in an autoclave. CLAVIER's central purpose is to find the most appropriate groupings and configurations of parts (or loads) to maximize autoclave throughput yet ensure that parts are properly cured. CLAVIER uses CBR to match a list of parts that need to be cured against a library of previously successful loads and suggest the most appropriate next load. As one of the first fielded CBR systems, CLAVIER demonstrates that CBR is a practical technology that can be used successfully in domains where more traditional approaches are difficult to apply.


Applying Case-Based Reasoning to Manufacturing

AI Magazine

's central purpose is to find the most The use of composite materials, Composite part fabrication requires two especially in aerospace applications, is on the major steps: layup and curing. Layup is the increase because of their unique weight and painstaking process in which multiple layers strength qualities. Depending on the orientation of graphite and fiberglass composite material of the graphite fibers, a part can be are fitted by hand on the exterior of a contoured extremely flexible in one direction but rigid mold. In addition, a part made from takes from two to seven days, depending on composite material is both lighter and the size of the mold and the skill of the technician. The increased use of In the second step, curing, the molded graphite parts, as well as the high cost of a composite material is hardened by pressurized spoiled part (as much as $50,000 for a single heating in a large convection autoclave.


AAAI-93 Workshops: Summary Reports

AI Magazine

The Association for the Advancement of Artificial Intelligence sponsored a number of workshops in conjunction with the Eleventh National Conference on Artificial Intelligence held 11-15 July 1993 in Washington, D.C. This article contains reports of four of the workshops that were conducted: AI Models for System Engineering, Case-Based Reasoning, Reasoning about Function, and Validation and Verification of Knowledge Based Systems.


AAAI-93 Workshops: Summary Reports

AI Magazine

The Association for the Advancement of Artificial Intelligence sponsored a number of workshops in conjunction with the Eleventh National Conference on Artificial Intelligence held 11-15 July 1993 in Washington, D.C. This article contains reports of four of the workshops that were conducted: AI Models for System Engineering, Case-Based Reasoning, Reasoning about Function, and Validation and Verification of Knowledge Based Systems.


Goal-Driven Learning: Fundamental Issues: A Symposium Report

AI Magazine

In his model, requirements needs, it must be able to represent is done unintentionally; a problem for filling system knowledge solver attempting to solve a gaps also direct explanation generation what these needs are. Ram proposed problem simply stores a trace of its by guiding retrieval and revision representations that include processing without attention to its of explanations during case-based the desired knowledge (possibly partially future relevance. However, Ng's previously explanation construction (Leake specified) and the reason that mentioned studies show that 1992). In the context of analogical the knowledge is sought. Leake for a different class of task, learning mapping, Thagard pointed out that focused on the representation of the goals have a strong effect on the goals, semantic constraints, and syntactic knowledge required to resolve anomalies learning performance of human constraints all affect analogical (which depends on a vocabulary learners. A future question is to identify mapping (Holyoak and Thagard 1989) of anomaly characterization structures the limits of goal-driven processing and the retrieval of potential analogs to describe the information in human learners.