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In this paper and attached video, we present a third-generation expert system named Knowledge Amplification by Structured Expert Randomization (KASER) for which a patent has been filed by the U.S. Navy's SPAWAR Systems Center, San Diego, CA (SSC SD). KASER is a creative expert system. It is capable of deductive, inductive, and mixed derivations. Its qualitative creativity is realized by using a tree-search mechanism. The system achieves creative reasoning by using a declarative representation of knowledge consisting of object trees and inheritance. KASER computes with words and phrases. It possesses a capability for metaphor-based explanations. This capability is useful in explaining its creative suggestions and serves to augment the capabilities provided by the explanation subsystems of conventional expert systems. KASER also exhibits an accelerated capability to learn. However, this capability depends on the particulars of the selected application domain. For example, application domains such as the game of chess exhibit a high degree of geometric symmetry. Conversely, application domains such as the game of craps played with two dice exhibit no predictable pattern, unless the dice are loaded. More generally, we say that domains whose informative content can be compressed to a significant degree without loss (or with relatively little loss) are symmetric. Incompressible domains are said to be asymmetric or random. The measure of symmetry pins the measure of randomness must always sum to unity. Index Terms--Expert systems, knowledge amplification, machine learning, object-oriented design, randomization.

This paper examines the problem of predicting the timing behavior of knowledge-based systems for real-time applications. In particular, we describe a suite of tools which analyze OPS5 programs to understand their timing properties. First, a graphical representation of an OPS5 program is defined and evaluated. This graph represents the logical control flows of an OPS5 program. Most of our analysis is based on this data structure. Second, we describe a novel tool which verifies that an OPS5 program can terminate in finite time. If the termination of the OPS5 program is not expected, the 'culprit' conditions are detected. These conditions are then used to correct the problem by adding extra rules to the original program. Third, another tool is introduced to aid timing analysis of OPS5 programs. This tool generates a set of test data which maximize the program execution time. Other functions are also provided to facilitate the timing analysis. Index Terms--Timing analysis, response time, OPS5, KBS, expert systems, rule-based systems, production systems, real-time systems.

Abstract The premise of this paper is that the key to problem solving is adequately representing the pro b/em to be solved. Most research has focused on how problems are […]

This paper investigates the application of support vector machines (SVMs) in texture classification. Instead of relying on an external feature extractor, the SVM receives the gray-level values of the raw pixels, as SVMs can generalize well even in high-dimensional spaces. Furthermore, it is shown that SVMs can incorporate conventional texture feature extraction methods within their own architecture, while also providing solutions to problems inherent in these methods. One-against-others decomposition is adopted to apply binary SVMs to multitexture classification, plus a neural network is used as an arbitrator to make final classifications from several one-against-others SVM outputs. Experimental results demonstrate the effectiveness of SVMs in texture classification. Index Terms--Support vector machines, texture analysis, pattern classification, machine learning, feature extraction.

Market strategy development through the utilization of the Delphi method, expert systems and fuzzy logic is discussed.

The development of any micro or small hydro plant requires some preliminary considerations to study the feasibility of the project. Different expertise required at this first stage and awareness about legal and governmental issues make the feasibility study an expensive and time-consuming task for many who might like to examine such opportunities. To solve this problem and make both the technical and legal issues behind a hydropower development accessible and understandable to everyone, an expert system named Small Hydropower Advisor (SHA) was developed. Unlike usual expert systems that deal with specific tasks in a domain area, SHA not only involves different required expertise, but also avoids technical terminology (as much as possible) to keep the consultation as simple and understandable as possible to any inexpert user. This paper explains SHA from the application and user perspective.