In artificial intelligence (AI), an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural programming code. Expert systems were among the first truly successful forms of AI software. They were created in the 1970s and then proliferated in the 1980s, being then widely regarded as the future of AI — before the advent of successful artificial neural networks. An expert system is divided into two subsystems: 1) a knowledge base, which represents facts and rules; and 2) an inference engine, which applies the rules to the known facts to deduce new facts, and can include explaining and debugging abilities.
Knowledge representation and reasoning is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can use to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge, in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning.
In computer science, a knowledge base (KB) is a set of sentences, each sentence given in a knowledge representation language, with interfaces to tell new sentences and to ask questions about what is known, where either of these interfaces might use inference. It is a technology used to store complex structured data used by a computer system. The initial use of the term was in connection with expert systems, which were the first knowledge-based systems.
Rapid application development (RAD), also called rapid application building (RAB), is both a general term for adaptive software development approaches, and the name for James Martin's method of rapid development. In general, RAD approaches to software development put less emphasis on planning and more emphasis on an adaptive process. Prototypes are often used in addition to or sometimes even instead of design specifications.
Usability can be described as the capacity of a system to provide a condition for its users to perform the tasks safely, effectively, and efficiently while enjoying the experience. In software engineering, usability is the degree to which a software can be used by specified consumers to achieve quantified objectives with effectiveness, efficiency, and satisfaction in a quantified context of use.
In the field of artificial intelligence, an inference engine is a software component of an intelligent system that applies logical rules to the knowledge base to deduce new information. The first inference engines were components of expert systems. The typical expert system consisted of a knowledge base and an inference engine. The knowledge base stored facts about the world. The inference engine applied logical rules to the knowledge base and deduced new knowledge. This process would iterate as each new fact in the knowledge base could trigger additional rules in the inference engine. Inference engines work primarily in one of two modes either special rule or facts: forward chaining and backward chaining. Forward chaining starts with the known facts and asserts new facts. Backward chaining starts with goals, and works backward to determine what facts must be asserted so that the goals can be achieved.
Knowledge engineering (KE) refers to all aspects involved in knowledge-based systems.
Forward chaining is one of the two main methods of reasoning when using an inference engine and can be described logically as repeated application of modus ponens. Forward chaining is a popular implementation strategy for expert systems, business and production rule systems. The opposite of forward chaining is backward chaining.
In systems engineering, information systems and software engineering, the systems development life cycle (SDLC), also referred to as the application development life cycle, is a process for planning, creating, testing, and deploying an information system. The SDLC concept applies to a range of hardware and software configurations, as a system can be composed of hardware only, software only, or a combination of both. There are usually six stages in this cycle: requirement analysis, design, development and testing, implementation, documentation, and evaluation.
Failure mode and effects analysis is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. For each component, the failure modes and their resulting effects on the rest of the system are recorded in a specific FMEA worksheet. There are numerous variations of such worksheets. An FMEA can be a qualitative analysis, but may be put on a quantitative basis when mathematical failure rate models are combined with a statistical failure mode ratio database. It was one of the first highly structured, systematic techniques for failure analysis. It was developed by reliability engineers in the late 1950s to study problems that might arise from malfunctions of military systems. An FMEA is often the first step of a system reliability study.
A knowledge-based system (KBS) is a computer program that reasons and uses a knowledge base to solve complex problems. Knowledge-based systems were the focus of early artificial intelligence researchers in the 1980s. The term can refer to a broad range of systems. However, all knowledge-based systems have two defining components: an attempt to represent knowledge explicitly, called a knowledge base, and a reasoning system that allows them to derive new knowledge, known as an inference engine.
A business rules engine is a software system that executes one or more business rules in a runtime production environment. The rules might come from legal regulation, company policy, or other sources. A business rule system enables these company policies and other operational decisions to be defined, tested, executed and maintained separately from application code.
User interface (UI) design or user interface engineering is the design of user interfaces for machines and software, such as computers, home appliances, mobile devices, and other electronic devices, with the focus on maximizing usability and the user experience. In computer or software design, user interface (UI) design primarily focuses on information architecture. It is the process of building interfaces that clearly communicate to the user what's important. UI design refers to graphical user interfaces and other forms of interface design. The goal of user interface design is to make the user's interaction as simple and efficient as possible, in terms of accomplishing user goals.
Paperback Software International Ltd. was a software company founded in 1983 by Adam Osborne to manufacture discount software such as word processor Paperback Writer and related spell checker Paperback Speller, spreadsheet VP-Planner, database VP-Info, and the VP-Expert artificial intelligence software. VP-Expert was developed by Brian Sawyer The company was headquartered in Berkeley, California.
The Common Lisp Interface Manager (CLIM) is a Common Lisp-based programming interface for creating user interfaces, i.e., graphical user interfaces (GUIs). It provides an application programming interface (API) to user interface facilities for the programming language Lisp. It is a fully object-oriented programming user interface management system, using the Common Lisp Object System (CLOS) and is based on the mechanism of stream input and output. There are also facilities for output device independence. It is descended from the GUI system Dynamic Windows of Symbolics' Lisp machines between 1988 and 1993.
... you can check out Common Lisp Interface Manager (CLIM). A descendant of the Symbolics Lisp machines GUI framework, CLIM is powerful but complex. Although many commercial Common Lisp implementations actually support it, it doesn't seem to have seen a lot of use. But in the past couple years, an open-source implementation of CLIM, McCLIM – now hosted at Common-Lisp.net – has been picking up steam lately, so we may be on the verge of a CLIM renaissance. – From Practical Common Lisp
Knowledge Engineering Environment (KEE) is a frame-based development tool for expert systems. 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. This version was available on several different UNIX workstations.
Spacecraft Health Inference Engine (SHINE) is a software-development tool for knowledge-based systems, created by the Artificial intelligence Group, Information Systems Technology Section at NASA/JPL. The system is in use in basic and applied AI research at JPL. SHINE was designed to operate in a real-time environment. It is written in Common LISP, but able to be utilized by non-LISP applications written in conventional programming languages such as C and C++. These non-LISP applications can be running in a distributed computing environment on remote computers or on a computer that supports multiple programming languages. SHINE provides a variety of facilities for the development of software modules for the primary functions in knowledge-based reasoning engines. The system may be used to develop artificial intelligence applications as well as specialized tools for research efforts.
In software engineering, a software development process or software development life cycle is a process of planning and managing software development. It typically involves dividing software development work into smaller, parallel, or sequential steps or sub-processes to improve design and/or product management. The methodology may include the pre-definition of specific deliverables and artifacts that are created and completed by a project team to develop or maintain an application.
VP/MS is a family of software components developed by CSC that support product development and product lifecycle management. Insurance companies use VP/MS to manage the rules, clauses, formulas and calculations associated with savings and both life and non-life insurance products. With VP/MS all calculations and queries for purposes such as quotes and administration are supported by a central repository of product definitions.
In information technology a reasoning system is a software system that generates conclusions from available knowledge using logical techniques such as deduction and induction. Reasoning systems play an important role in the implementation of artificial intelligence and knowledge-based systems.
