1 Intelligent Systems Q: Where to start? A: At the beginning (1940) by Denis Riordan Reference Modern Artificial Intelligence began in the middle of the.

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Presentation transcript:

1 Intelligent Systems Q: Where to start? A: At the beginning (1940) by Denis Riordan Reference Modern Artificial Intelligence began in the middle of the last century. Alan Turing proposed the question, ‘Can machines think?’ A QUARTERLY REVIEW OF PSYCHOLOGY AND PHILOSOPHY, Computing machinery and intelligence - A. M. Turing, p.433, VOL. LIX. No.236. October,

General References Find some of your own! 2 [1] Negnevitsky M., Artificial Intelligence, A Guide to Intelligent Systems, 2011 [2] Russell S. and Norvig P., Artificial Intelligence, A Modern Approach [3] Udacity, [4] Hodges A., “The Alan Turing Home Page”, [5] Association for the Advancement of Artificial Intelligence, [6] Stone and Hirsh, “Artificial Intelligence: The Next Twenty-Five Years”, article /view/1852/1750 [7] IBM’s Watson Program on Jeopardy, [8] IBMWatson.

3 Goals of the Course 1.To understand different views of AI 2.To apply algorithms from AI to solve some real world problems

Exercise Give a (your) definition of intelligence (three lines)? thinks like a human thinks rationally acts like human acts rationally 4 Give your definition of AI (three lines)?

Approaches to AI thinking humanly – cognitive modeling acting humanly - Turing thinking rationally – logicians acting rationally – achieve the best outcome 5

6 Class Exercise Use your your definition. According to your definition: Give an example of an interesting intelligent system that you have encountered? Explain? Can your definition be used to decide, for example, whether an extraterrestrial radio signal indicates an alien intelligence? See -

Everyday use of AI Games Medicine Finance The Web Robotics Give some other 7

Agent Model Agent Environment Actuator (action) Sensor (percept) Performance Measure 8

Minimal Agent 9

Properties of Environments Observability (full vs partial) Uncertainty (deterministic vs stochastic) Experience (episodic vs sequential) Change (static vs dynamic) Continuity (discrete vs continuous) Single vs Multiagent 10

Learning Agent 11

RATIONAL AGENT Agent that selects an action to maximize performance given a percept sequence and knowledge base 12

13 Class Exercise Measures of Intelligence

14 Some AI Problems in Research Represent medical knowledge for health diagnostics and treatment planning Game Players that learn from scratch Encyclopedia on Demand – Produce a 5000 word encyclopedia style article, on a given subject, by summarizing from the relevant information on the web Robot drivers – taxi Natural Language Understanding

15 Examples of AI Uses in Industry Remote Diagnostics Healthcare, clinical guidelines and pathways Implementing Business Rules Data Mining Natural language Product selection

16 What are we trying to accomplish? The study of how to make agents that do things at which, for the moment, people are better (adapted: Rich and Knight, 1991)

17 Schools of thought? Success compared to human performance. Focus on mechanisms, structure Evolution Swarm Intelligence

18 Turing Test The computer should be interrogated by a human via a teletype and passes if the interrogator cannot tell if there is a human or a computer at the other end

19 Turing Test: Phase 1

20 Turing Imitation Game: Phase 2 n In the second phase of the game, the man is replaced by a computer programmed to deceive the interrogator as the man did.

21 Turing Imitation Game: Phase 2

22 The Turing test is objective By maintaining communication between the human and the machine via terminals, the test gives us an objective standard view on intelligence.

23 Turing’s Prediction In 1946 Turing predicted that by 2000 a computer could be programmed to have a conversation with a human interrogator for five minutes and would have a 30% chance of deceiving the interrogator that it was human.

24 Approaches to AI 1.Alan Turing defined intelligent behavior as the ability to achieve human level performance in cognitive tasks, sufficient to fool an interrogator 2.Minsky defined intelligence in terms of mechanisms. e.g., a human is a 'meat' machine 3.More recently some scientists have come to view intelligence as a evolutionary process - evolving in a competitive environment. The more competitive the more intelligent. 4.Swarm Intelligence

25 Class Exercise How does your definition of machine intelligence given earlier fit in with the four approaches given above ?