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Introduction to Artificial Intelligence - IAT 813 at Simon Fraser University

Explore the fundamentals of Artificial Intelligence (AI) in this comprehensive course at Simon Fraser University, IAT 813, led by Steve DiPaola. Designed for mixed graduate students, this course covers essential AI topics such as algorithms, machine learning, automated reasoning, and more while minimizing complex mathematics. You will gain a solid understanding of AI's origins, capabilities, and current applications. The course aims to equip you with practical techniques for solving computational problems, preparing you for industry or academic pursuits in the realm of intelligent systems.

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Introduction to Artificial Intelligence - IAT 813 at Simon Fraser University

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  1. Artificial Intelligence0. Course Overview Course IAT813 Simon Fraser University Steve DiPaola Material adapted : S. Colton / Imperial C.

  2. Designed Especially for You • Designed for Mixed Graduate Students • Broad coverage of topics • Less background in computing, e.g., logic • Attempt to avoid complex maths • Focus on algorithmic details • Material adapted: upcoming book by Colton, UK

  3. Quick Questions about AI • What is Artificial Intelligence? • Tough question (because AI is young) • Quick answer: getting machines to do smart things • Where did Artificial Intelligence originate? • AI is not “owned” by computer science • Origins in (at least): math, logic, computer science, philosophy, psychology, cognitive science, biology • Understanding intelligence one of the oldest questions • Turing introduced AI notions in his seminal work • “AI” coined by John McCarthy in Dartmouth, 1956

  4. Common Misconceptions • From popular science/science fiction/media • Robots will take over the earth • Kevin Warwick • Computers will never be intelligent • Roger Penrose • Humans will choose to become computers • Ray Kurzweil • Computers will evolve to be human • Mark Jeffery

  5. Course Aims • Assumption: • You will be going off to industry/academia • Will come across computational problems • requiring intelligence (in humans and computers) to solve • Two aims: • Give you an understanding of what AI is • Aims, abilities, methodologies, applications, … • Equip you with techniques for solving problems • By writing/building intelligent software/machines

  6. Course Overview: four areas • AI fundamentals • Characterisations, terminology, methodologies • Representation and search • Application to game playing • Automated reasoning (deduction) • Socrates was mortal • Machine learning (induction) • Every man has died, so we all die • Evolutionary algorithms • Breed your own programs

  7. Administration • My details • Steve DiPaola (sdipaola@sfu.ca), office 2nd fl 2808 • Course Website: • http://www.sfu.ca/iat813 • Course details • Seminar Thurs 2:30 - 5:20PM • Room 2990 Office Hours Thurs 1pm-

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