1 / 25

Intelligent Systems

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?’

mairi
Télécharger la présentation

Intelligent Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

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, 1950 http://www.abelard.org/turpap/turpap.php

  2. General ReferencesFind some of your own! [1] Negnevitsky M., Artificial Intelligence, A Guide to Intelligent Systems, 2011 [2] Russell S. and Norvig P., Artificial Intelligence, A Modern Approach [3] Udacity, https://www.udacity.com/course/cs271 [4] Hodges A. , “The Alan Turing Home Page”, http://www.turing.org.uk/turing/ [5] Association for the Advancement of Artificial Intelligence, http://www.aaai.org/home.html [6] Stone and Hirsh, “Artificial Intelligence: The Next Twenty-Five Years” , http://www.aaai.org/ojs/index.php/aimagazine/article/view/1852/1750 [7] IBM’s Watson Program on Jeopardy, http://www.aaai.org/AITopics/pmwiki/pmwiki.php/AITopics/HomePage [8] IBMWatson. http://www-03.ibm.com/innovation/us/watson/index.shtml 2

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

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

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

  6. Class ExerciseUse 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 - http://www.planetary.org/programs/projects/setiathome/

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

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

  9. Minimal Agent

  10. 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

  11. Learning Agent

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

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

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

More Related