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Knowledge Engineering Environment (KEE) is a frame-based development tool for expert systems. [1] It was developed and sold by IntelliCorp, and was first released in 1983.It ran on Lisp machines, and was later ported to Lucid Common Lisp with the CLX library, an X Window System (X11) interface for Common Lisp.
The first public release of Crack was version 2.7a, which was posted to the Usenet newsgroups alt.sources and alt.security on 15 July 1991. Crack v3.2a+fcrypt, posted to comp.sources.misc on 23 August 1991, introduced an optimised version of the Unix crypt() function but was still only really a faster version of what was already available in other packages.
An expert system is an example of a knowledge-based system. Expert systems were the first commercial systems to use a knowledge-based architecture. In general view, an expert system includes the following components: a knowledge base, an inference engine, an explanation facility, a knowledge acquisition facility, and a user interface. [48] [49]
Installation (or setup) of a computer program (including device drivers and plugins), is the act of making the program ready for execution.Installation refers to the particular configuration of software or hardware with a view to making it usable with the computer.
Mixture of experts (MoE) is a machine learning technique where multiple expert networks (learners) are used to divide a problem space into homogeneous regions. [1] MoE represents a form of ensemble learning .
Stat-Ease released its first version of Design–Expert in 1988. In 1996 the firm released version 5 which was the first version of the software designed for Microsoft Windows. [3] Version 6.0 moved to a full 32-bit architecture and fuller compliance with Windows visual convention and also allowed up to 256 runs for two-level blocked designs. [4]
For example, MYCIN was an early expert system for medical diagnosis and EMYCIN was an inference engine extrapolated from MYCIN and made available for other researchers. [1] As expert systems moved from research prototypes to deployed systems there was more focus on issues such as speed and robustness.
Machine vision is the technology and methods used to provide imaging-based automatic inspection and analysis for such applications as automatic inspection, process control, and robot guidance, usually in industry. Machine vision refers to many technologies, software and hardware products, integrated systems, actions, methods and expertise.