We propose a model of the development of geometric reasoning in children that explicitly involves learning. The model uses a neural network that is initialized with an understanding of geometry similar to that of second-grade children. Through the presentation of a series of examples, the model is shown to develop an understanding of geometry similar to that of fifth-grade children who were trained using similar materials.

Recently, both connectionist and symbolic methods have been developed for biasing learning with prior knowledge lFu, 1989; Towell et a/., 1990; Ourston and Mooney, 1990]. Most ofthese methods revise an imperfect knowledge base (usually obtained from a domain expert) to fit a set of empirical data. Some of these methods have been successfully applied to real-world tasks, such as recognizing promoter sequences in DNA [Towell et ai., 1990; Ourston and Mooney, 1990]. The results demonstrate that revising an expert-given knowledge base produces more accurate results than learning from training data alone.

We propose a model of the development of geometric reasoning in children that explicitly involves learning. The model uses a neural network that is initialized with an understanding of geometry similar to that of second-grade children. Through the presentation of a series of examples, the model is shown to develop an understanding of geometry similar to that of fifth-grade children who were trained using similar materials.

Recently, both connectionist and symbolic methods have been developed for biasing learning with prior knowledge lFu, 1989; Towell et a/., 1990; Ourston and Mooney, 1990]. Most ofthese methods revise an imperfect knowledge base (usually obtained from a domain expert) to fit a set of empirical data. Some of these methods have been successfully applied to real-world tasks, such as recognizing promoter sequences in DNA [Towell et ai., 1990; Ourston and Mooney, 1990]. The results demonstrate that revising an expert-given knowledge base produces more accurate results than learning from training data alone.

We propose a model of the development of geometric reasoning in children that explicitly involves learning. The model uses a neural network that is initialized with an understanding of geometry similar to that of second-grade children. Through the presentation of a series of examples, the model is shown to develop an understanding of geometry similar to that of fifth-grade children who were trained using similar materials.

Recently, both connectionist and symbolic methods have been developed for biasing learning with prior knowledge lFu,1989; Towell et a/., 1990; Ourston and Mooney, 1990]. Most ofthese methods revise an imperfect knowledge base (usually obtained from a domain expert) to fit a set of empirical data. Some of these methods have been successfully applied to real-world tasks, such as recognizing promoter sequences in DNA [Towell et ai., 1990; Ourston and Mooney, 1990]. The results demonstrate that revising an expert-given knowledge base produces more accurate results than learning from training data alone. Inthis paper, we describe the RAPTURE system (Revising Approximate 107 108 Mahoney and Mooney Probabilistic Theories Using Repositories of Examples), which combines connectionist andsymbolic methods to revise both the parameters and structure of a certainty-factor rule base. 2 The Rapture Algorithm

Celite corporation and Andersen Consulting have developed an advanced approach to traditional software development called the application software factory (ASF)." The approach is an integration of technology and total quality "management" techniques that includes the use of an expert system to guide module design and perform "module programming." The expert system component is called the knowledge-based design assistant and its inclusion in the ASF methodology" has significantly reduced module development time, training time, and module and communication errors.

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.

This project has entered into a joint agreement agreements with Nestor Inc. (Providence, will involve simulating fires in buildings with software giant Microsoft Corp. R.I.) to institute pilot projects and assessing how a VR system as the first step toward installing (Redmond, Wash.) that will enable Planet is an expert system that individual cardholders and banks provides strategic and detailed planning against losses due to fraud, making for financial audits. It produces Bank Bandeirantes (Sao Paulo, Brazil) use of neural networks to learn a cardholder's risk assessments for a variety of financial has teamed up with another Brazilian pattern of credit card use. Venus is a flowcharting tool analysis expert system that operates in Cal.) will team up with VRl Entertainment for auditors who specialize in auditing real-time. The intelligent system has Inc. (Boulder, Colo.) to computer systems running deliver virtual reality to the home via helped the bank experience dramatic SIRIUS (SWIFT's Intelligent examines in detail a P 1 the key AI technologies: telecommunications operators Contact Lionheart Publishing system supervises the 150 switches Inc,2555 Cumberland Parkway, an event manager and hypertext Suite 299, Atlanta, GA 30339, (404) 434-manuals, and fields hundreds of telephone and 350 connections that make up 2187, FAX: (404) 432-6969. Wash.) have teamed up to develop Intelligent Alarming, which integrates Metropolitan Federal Bank (Edina, Mitek Systems (San Diego, Cal.) has industrial automation software Minn.) has deployed an automated completed a test phase for an automatic with an expert system.

Celite corporation and Andersen Consulting have developed an advanced approach to traditional software development called the application software factory (ASF)." The approach is an integration of technology and total quality "management" techniques that includes the use of an expert system to guide module design and perform "module programming." The expert system component is called the knowledge-based design assistant and its inclusion in the ASF methodology" has significantly reduced module development time, training time, and module and communication errors.