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Knowledge based systems -- introduction


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Knowledge based systems -- introduction

  1. 1. Knowledge-Based Systems: Introduction Richard Dybowski 5 Feb 2008 Russell & Norvig (2003), Chapter 1
  2. 2. Aims● To understand the concept of AI in termsof a rational agent● To appreciate AIs history and ability
  3. 3. Artificial Intelligence (AI)AI attempts not just to understand how we think butalso to build intelligent entities by attempting tosystemise and automate intellectual tasks.AI encompasses many subjects from general-purpose areas, such as learning and perception, tospecific tasks such as playing chess anddiagnosing diseases.
  4. 4. Publics perception of AI “2001: A Space Odyssey”“Artificial Intelligence: AI” “Halo 3”
  5. 5. “But what exactly is AI?”There are different answersto this question (depending on who you ask)
  6. 6. Russell & Norvig (2003) classification of eight AIdefinitions: A rational system does the “right thing” given what it knows
  7. 7. The “rational agent” approachBest approach because:(a) More general than “laws of thought approach”because rationality is not only about correct inference(b) More amenable to scientific development thanapproaches based on human behaviour or humanthought
  8. 8. History of AIGestation (1943 – 1955):McCulloc & Pitts (1943) – artificial neuronsHebbian learning (1949)Turing test (1950)Birth of AI (1956):1956 Workshop at Dartmouth CollegeEarly enthusiasm (1952-1969):Many limited successes; e.g., General Theorem Prover,LISP, microworld problem solvers
  9. 9. History of AI (continued)A dose of reality (1966 – 1973):Early systems failed on more difficult problemsKnowledge-based systems (1969 – present):DENDRAL (1099); MYCIN (1980); etcAI becomes an industry (1980 - present):R1 (1982) - first commercial expert systembut followed by “AI Winter”Return of neural networks (1986 - present):Back-propagation building algorithm (1986)
  10. 10. History of AI (continued)AI becomes a science (1987 – present):● Scientific method adopted● Common to build on existing theories● Claims based on rigorous theorems or hardexperimental evidence● Relevant to real-world applicationsThe emergence of intelligent agents (1995 – present):“Bots” on the Internet
  11. 11. The state of the artWhat can AI do today?Examples:● Machine planning; e.g. NASAs Remote Agent (2000) –monitors spacecraft operations● IBMs Deep Blue (1997) – beat Kasparov● Lymphatic cancer diagnosis (1991) – beat an expert!