GC: n
CT: Expert Systems are computer programs that are derived from a branch of computer science research called Artificial Intelligence (AI). AI’s scientific goal is to understand intelligence by building computer programs that exhibit intelligent behavior. It is concerned with the concepts and methods of symbolic inference, or reasoning, by a computer, and how the knowledge used to make those inferences will be represented inside the machine.
Of course, the term intelligence covers many cognitive skills, including the ability to solve problems, learn, and understand language; AI addresses all of those. But most progress to date in AI has been made in the area of problem solving – concepts and methods for building programs that reason about problems rather than calculate a solution.
AI programs that achieve expert-level competence in solving problems in task areas by bringing to bear a body of knowledge about specific tasks are called knowledge-based or expert systems. Often, the term expert systems is reserved for programs whose knowledge base contains the knowledge used by human experts, in contrast to knowledge gathered from textbooks or non-experts. More often than not, the two terms, expert systems (ES) and knowledge-based systems (KBS), are used synonymously. Taken together, they represent the most widespread type of AI application. The area of human intellectual endeavor to be captured in an expert system is called the task domain. Task refers to some goal-oriented, problem-solving activity. Domain refers to the area within which the task is being performed. Typical tasks are diagnosis, planning, scheduling, configuration and design. An example of a task domain is aircraft crew scheduling, discussed in Chapter 2.
Building an expert system is known as knowledge engineering and its practitioners are called knowledge engineers. The knowledge engineer must make sure that the computer has all the knowledge needed to solve a problem. The knowledge engineer must choose one or more forms in which to represent the required knowledge as symbol patterns in the memory of the computer – that is, he (or she) must choose a knowledge representation. He must also ensure that the computer can use the knowledge efficiently by selecting from a handful of reasoning methods. The practice of knowledge engineering is described later. We first describe the components of expert systems.
S: http://www.wtec.org/loyola/kb/c1_s1.htm (last access: 28 December 2014)
N: 1. expert (adj): late 14c., “having had experience; skillful,” from Old French expert, espert “experienced, practiced, skilled” and directly from Latin expertus (contracted from experitus), “tried, proved, known by experience,” past participle of experiri “to try, test” (see experience). The adjective tends to be accented on the second syllable, the noun on the first. Related: Expertly; expertness.
system (n): 1610s, “the whole creation, the universe,” from Late Latin systema “an arrangement, system,” from Greek systema “organized whole, a whole compounded of parts,” from stem of synistanai “to place together, organize, form in order,” from syn- “together” + root of histanai “cause to stand” from PIE root sta- “to stand” (see stet).
Meaning “set of correlated principles, facts, ideas, etc.” first recorded 1630s. Meaning “animal body as an organized whole, sum of the vital processes in an organism” is recorded from 1680s; hence figurative phrase to get (something) out of one’s system (1900). Computer sense of “group of related programs” is recorded from 1963. All systems go (1962) is from U.S. space program. The system “prevailing social order” is from 1806.
2. An expert system, sometimes known as artificial intelligence, is a computer program that simulates the knowledge and judgment of humans.
3. Expert system is a somewhat archaic term that describes a computer program that simulates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field.
Now, more commonly known as AI, or artificial intelligence, expert systems have a long history dating back to the 1960s and 1970s. But typically, such a system incorporates a knowledge base containing accumulated experience and an inference or rules engine – a set of rules for applying the knowledge base to each particular situation that is described to the program. Sophisticated expert systems can be enhanced with additions to the knowledge base or to the set of rules.
Expert systems have played a large role in financial services, healthcare, manufacturing and video games.
S: 1. OED – http://www.etymonline.com/index.php?allowed_in_frame=0&search=expert&searchmode=none; http://www.etymonline.com/index.php?allowed_in_frame=0&search=system&searchmode=none (last access: 28 December 2014). 2 & 3. http://searchhealthit.techtarget.com/definition/expert-system (last access: 28 December 2014).
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CR: artificial intelligence, computational intelligence, computer science, explanation subsystem, knowledge-based system.
