Artificial Intelligence Discipline

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An Artificial Intelligence Discipline is a computing science subdiscipline that focuses on the AI subject area (the creation of intelligent machines that can solve an intelligence task).




  • (Wikipedia, 2012) ⇒
    • QUOTE:Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1956, defines it as "the science and engineering of making intelligent machines."[1]

      The field was founded on the claim that a central property of humans, intelligence — the sapience of Homo sapiens — can be so precisely described that it can be simulated by a machine.[2] This raises philosophical issues about the nature of the mind and the ethics of creating artificial beings, issues which have been addressed by myth, fiction and philosophy since antiquity.[3] Artificial intelligence has been the subject of optimism,[4] but has also suffered setbacks[5] and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.

      AI research is highly technical and specialized, deeply divided into subfields that often fail in the task of communicating with each other. Subfields have grown up around particular institutions, the work of individual researchers, and the solution of specific problems, resulting in longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. General intelligence (or “strong AI") is still among the field's long term goals.

  1. Cite error: Invalid <ref> tag; no text was provided for refs named McCarthy's definition of AI
  2. See the Dartmouth proposal, under Philosophy, below.
  3. Cite error: Invalid <ref> tag; no text was provided for refs named McCorduck's thesis
  4. The optimism referred to includes the predictions of early AI researchers (see optimism in the history of AI) as well as the ideas of modern transhumanists such as Ray Kurzweil.
  5. The "setbacks" referred to include the ALPAC report of 1966, the abandonment of perceptrons in 1970, the Lighthill Report of 1973 and the collapse of the lisp machine market in 1987.