Outline: Introduction to AI Artificial Intelligence N-ways Introduction Introduction to AI - Personal Information and - What is Intelligence? Introduction Background - An Intelligent Entity - The Age of Intelligent Machines Course Outline: - Definitions of AI - Requirements and Expectation - Behaviourist’s View on Intelligent - Module Assessment Machines - Recommended Books - Turing’s Test - Part 1 & 2 - Layout of Course (14 lessons) - History of AI Lecture 1 - Examples of AI systems - Office Hours Course Delivery Methods General Reference for the Course Goals and Objectives of module 2 Course Outline: General Reference for the Course Recommended Books Artificial Intelligence by Patrick Henry Winston AI related information. Whatis.com (Computer Science Dictionary) Logical Foundations of Artificial Intelligence by Michael R. http://whatis.com/search/whatisquery.html Genesereth, Nils J. Nislsson, Nils J. Nilsson General computer-related news sources. Technology Encyclopedia Artificial Intelligence, Luger, Stubblefield http://www.techweb.com/encyclopedia/ General Information Artificial Intelligence : A Modern Approach by Stuart J. Russell, Technology issues. Peter Norvig Computing Dictionary http://wombat.doc.ic.ac.uk/ Artificial Intelligence by Elaine Rich, Kevin Knight (good for All web links in my AI logic, knowledge representation, and search only) website. Webster Dictionary http://work.ucsd.edu:5141/cgi- bin/http_webster 3 4 Goals and Objectives of module Introduction to AI: What is Intelligence? Understand motivation, mechanisms, and potential Intelligence, taken as a whole, consists of of Artificial Intelligence techniques. the following skills:- Balance of breadth of techniques with depth of 1. the ability to reason understanding. 2. the ability to acquire and apply knowledge Conversant with the applicational scope and 3. the ability to manipulate and solution methodologies of AI. communicate ideas Knowledge in LISP. Ready to apply AI techniques to the practice. 5 6 1 Introduction to AI: Introduction to AI: An Intelligent Entity The Age of Intelligent Machines INTERNAL INPUTS 1st Industrial Revolution: the Age of Automation: PROCESSES Has knowledge Machines extend & multiply man's physical capabilities Senses environment Has understanding/ intentionality See Hear Can Reason 2nd Industrial Revolution: the Age of Info Tech: Touch Machines extend & multiply man's mental capabilities Taste Smell Information & Knowledge Revolution: the Age of Exhibits behaviour Knowledge Technology "..working smarter, not harder." OUTPUTS How do we make our systems smarter? - by building in intelligence 7 8 Introduction to AI: Introduction to AI: Definitions of AI Turing’s Test " ... the science of making machines do things that would In 1950 Alan Turing published his now require intelligence if done by humans" - Marvin Minsky famous paper "Computing Machinery and Intelligence." In that paper he describes a method for humans to test AI is the part of computer science concerned with AI programs. designing intelligent computer systems -E. In its most basic form, a human judge Feigenbaum sits at a computer terminal and interacts with the subject by written Systems that can demonstrate human-like reasoning communication only. The judge must capability to enhance the quality of life and improve then decide if the subject on the other end of the computer link is a human or business competitiveness - Japan-S’pore AI an AI program imitating a human. Centre http://www.turing.org.uk/turing/ 9 10 Introduction to AI: Introduction to AI: Turing’s Test - Part 1 Turing’s Test - Part 2 Part 2 - Woman, Machine & Judge. Which one’s the man? Which one’s the computer? If the computer succeeds in fooling A the judge then it has managed to B A exhibit a human level of intelligence B in the task of pretending to be a Part 1 - Woman, Man & Judge. woman, the definition of intelligence the machine has shown itself to be 11 intelligent. 12 2 Introduction to AI: Introduction to AI: History of AI History of AI (cont’d) Important research that laid the groundwork for AI: Basic philosophy is recorded since ancient Greece 1900-50s: formal grammar & language theories Early push after computer discovered (50's): Connectionist (neural net) vs. Symbolist/Logicist (AI) 1920-30s: formalisation of reasoning (predicate calculus and 1956 - recognised as the official beginning of AI - The Dartmouth propositional logic) Summer Workshop 1940-50s: Cybernetics - communication in man and The 1950s was also noted for chess playing programs, machine machine translation, automatic theorem provers, Chomsky generative grammars and LISP 1950s: reality of digital computers (Mark I, ENIAC, EDVAC and UNIVAC) CMU, Stanford, and IBM Others: Information Theory, Neurological Theories, Boolean Early successes and enthusiasm - neural learning, theorem provers, Algebra, etc. 13 problem solvers (GPS), game players, etc. 14 Introduction to AI: Introduction to AI: History of AI (cont’d) Examples of AI systems Robots Game Playing Dartmouth Machine Translation Degree New Chess-playing program Conference Resource Scheduling of Japan 5th Technology Voice recognition system Motivation Generation Support Expert systems (diagnosis, Computer Speech recognition system advisory, planning, etc) AI Grammer checker Machine learning Winter Pattern recognition Intelligent interfaces 1948 1970s - 80s mid-1980s Time Medial diagnosis System malfunction rectifier Adapted from: Joe Carter (Andersen Consulting, 1988) Oliver Tian (Andersen Consulting, 1989) 15 16 Class Activity: AI and Us To discuss in groups on any AI-ish system(s) that the members are familiar with, some examples: End of Lecture 1 Robots System malfunction rectifier Chess-playing program Mars pathfinder Voice recognition system Good Day. Machine Translation Speech recognition system Resource Scheduling Grammar checker Expert systems Pattern recognition Machine learning Medial diagnosis Intelligent interfaces 17 3.