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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. First 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.
The waterfall model is a breakdown of development activities into linear sequential phases, meaning they are passed down onto each other, where each phase depends on the deliverables of the previous one and corresponds to a specialization of tasks. The approach is typical for certain areas of engineering design. In software development, it tends to be among the less iterative and flexible approaches, as progress flows in largely one direction through the phases of conception, initiation, analysis, design, construction, testing, deployment and maintenance. The waterfall model is the earliest SDLC approach that was used in software development.
The rational unified process (RUP) is an iterative software development process framework created by the Rational Software Corporation, a division of IBM since 2003. RUP is not a single concrete prescriptive process, but rather an adaptable process framework, intended to be tailored by the development organizations and software project teams that will select the elements of the process that are appropriate for their needs. RUP is a specific implementation of the Unified Process.
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.
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.
IDEF, initially an abbreviation of ICAM Definition and renamed in 1999 as Integration Definition, is a family of modeling languages in the field of systems and software engineering. They cover a wide range of uses from functional modeling to data, simulation, object-oriented analysis and design, and knowledge acquisition. These definition languages were developed under funding from U.S. Air Force and, although still most commonly used by them and other military and United States Department of Defense (DoD) agencies, are in the public domain.
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.
Web development is the work involved in developing a website for the Internet or an intranet. Web development can range from developing a simple single static page of plain text to complex web applications, electronic businesses, and social network services. A more comprehensive list of tasks to which Web development commonly refers, may include Web engineering, Web design, Web content development, client liaison, client-side/server-side scripting, Web server and network security configuration, and e-commerce development.
Computer-aided software engineering (CASE) is a domain of software tools used to design and implement applications. CASE tools are similar to and are partly inspired by computer-aided design (CAD) tools used for designing hardware products. CASE tools are intended to help develop high-quality, defect-free, and maintainable software. CASE software was often associated with methods for the development of information systems together with automated tools that could be used in the software development process.
MYCIN was an early backward chaining expert system that used artificial intelligence to identify bacteria causing severe infections, such as bacteremia and meningitis, and to recommend antibiotics, with the dosage adjusted for patient's body weight — the name derived from the antibiotics themselves, as many antibiotics have the suffix "-mycin". The Mycin system was also used for the diagnosis of blood clotting diseases. MYCIN was developed over five or six years in the early 1970s at Stanford University. It was written in Lisp as the doctoral dissertation of Edward Shortliffe under the direction of Bruce G. Buchanan, Stanley N. Cohen and others.
Dynamic systems development method (DSDM) is an agile project delivery framework, initially used as a software development method. First released in 1994, DSDM originally sought to provide some discipline to the rapid application development (RAD) method. In later versions the DSDM Agile Project Framework was revised and became a generic approach to project management and solution delivery rather than being focused specifically on software development and code creation and could be used for non-IT projects. The DSDM Agile Project Framework covers a wide range of activities across the whole project lifecycle and includes strong foundations and governance, which set it apart from some other Agile methods. The DSDM Agile Project Framework is an iterative and incremental approach that embraces principles of Agile development, including continuous user/customer involvement.
Software prototyping is the activity of creating prototypes of software applications, i.e., incomplete versions of the software program being developed. It is an activity that can occur in software development and is comparable to prototyping as known from other fields, such as mechanical engineering or manufacturing.
Object-oriented analysis and design (OOAD) is a technical approach for analyzing and designing an application, system, or business by applying object-oriented programming, as well as using visual modeling throughout the software development process to guide stakeholder communication and product quality.
Knowledge-based engineering (KBE) is the application of knowledge-based systems technology to the domain of manufacturing design and production. The design process is inherently a knowledge-intensive activity, so a great deal of the emphasis for KBE is on the use of knowledge-based technology to support computer-aided design (CAD) however knowledge-based techniques can be applied to the entire product lifecycle.
The incremental build model is a method of software development where the product is designed, implemented, and tested incrementally until the product is finished. It involves both development and maintenance. The product is defined as finished when it satisfies all of its requirements. This model combines the elements of the waterfall model with the iterative philosophy of prototyping. According to the Project Management Institute, an incremental approach is an "adaptive development approach in which the deliverable is produced successively, adding functionality until the deliverable contains the necessary and sufficient capability to be considered complete."
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.
Knowledge Acquisition and Documentation Structuring (KADS) is a structured way of developing knowledge-based systems. It was developed at the University of Amsterdam as an alternative to an evolutionary approach and is now accepted as the European standard for knowledge based systems.
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.
The Knowledge Based Software Assistant (KBSA) was a research program funded by the United States Air Force. The goal of the program was to apply concepts from artificial intelligence to the problem of designing and implementing computer software. Software would be described by models in very high level languages (essentially equivalent to first order logic) and then transformation rules would transform the specification into efficient code. The air force hoped to be able to generate the software to control weapons systems and other command and control systems using this method. As software was becoming ever more critical to USAF weapons systems it was realized that improving the quality and productivity of the software development process could have significant benefits for the military, as well as for information technology in other major US industries.
Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules, objects, and frame-based ontologies.
References
- ↑ Feigenbaum, Edward; McCorduk, Pamela (1983). The Fifth Generation (1st ed.). Reading, MA: Addison-Wesley. ISBN 978-0-201-11519-2. OCLC 9324691.
- ↑ Schreiber, August Th.; Akkermans, Hans; Anjewierden, Anjo; Dehoog, Robert; Shadbolt, Nigel; Vandevelde, Walter; Wielinga, Bob (2000), Knowledge engineering and management: the CommonKADS methodology (1st ed.), Cambridge, MA: The MIT Press, ISBN 978-0-262-19300-9
