An Introduction To Artificial Intelligence

A presentation at Lecture in April 2015 in by Shane Hudson

Slide 1

Slide 1

An Introduction To Artificial Intelligence It’s not all just robots! Discussion, what is AI? Identify AI challenges and non. Misconceptions.

Slide 2

Slide 2

A Few Questions • What do you think Artificial Intelligence is? • What is it used for? • Which AI systems have you used recently?

Slide 3

Slide 3

Alan Turing (23 June 1912 – 7 June 1954) Ask who recognises the photo.

Ask about things he is known for:

Enigma

Church Turing Thesis

Turing Machines

Turing Test

Slide 4

Slide 4

Alonzo Church (June 14, 1903 – August 11, 1995) Ask who this is, probably harder than previous.

Ask about things he is known for:

Church-Turing Thesis

Lambda Calculus

Undecidability of the Entscheidungsproblem

Turing’s doctoral advisor

Slide 5

Slide 5

Church Turing Thesis • In 1931, Kurt Gödel’s first incompleteness theorem proved that some true functions on integers cannot be computed. • The Church-Turing Thesis characterises exactly which functions can be computed. • It also states that a Turing machine is capable of computing any computable function.

Slide 6

Slide 6

Which Functions Are Not Computable? • Halting Problem

  • “Will this program finish running, or run forever?” 



 Proved by Alan Turing. • Decision Problem - “Is this statement provable, given true premises (axioms), using rules of logic?” 
 
 Proved by Alonzo Church.

Slide 7

Slide 7

Turing Machines • An abstract idea, not a real physical machine. • Works with infinite storage, such as a infinite tape of binary digits. • A ‘head’ looks at a cell on the tape, it can both read and write, and move left or right. • The turing machine has defined states, which tell the head what to do with the cell it is looking at.

Slide 8

Slide 8

Slide 9

Slide 9

Turing Machine Diagram https://www.youtube.com/watch?v=gJQTFhkhwPA q 1 q 2 q 0 q H 1/0,L 0/1,· 0/0,L 1/1,R 0/0,· 1/0,L Initial Something that they can work on practically.

Slide 10

Slide 10

How It Works • 1/0,L - If 1, change to 0 and move left • 0/1,R - If 0, change to 1 and move right • 0/0,· - If 0, keep as 0 and don’t move

Slide 11

Slide 11

q 1 q 2 q 0 q H 1/0,L 0/1,· 0/0,L 1/1,R 0/0,· 1/0,L Initial 0 1 0 0 1 1 1 0 1 Halt Do this in groups on paper.

Slide 12

Slide 12

Turing Test • In his 1950, Alan Turing published a paper to Mind journal titled ‘Computing Machinery and Intelligence’. • He discussed the idea of computers being able to think. • Most importantly, he proposed a test in which somebody (or multiple people) have a conversation with either a person or a machine without knowing which.
• If there is a high success rate of thinking the machine is a person, then the test is passed.

Slide 13

Slide 13

Oxford Dictionary “The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.” So, What Is Artificial Intelligence?

Slide 14

Slide 14

Some Categories of AI • Natural Computation • Computer Vision • Natural Language • Machine Learning • Simulation • Data Mining These are not official categories, because AI is such a loose term.

Slide 15

Slide 15

Slide 16

Slide 16

Slide 17

Slide 17

Neural Networks Talk about how each node is useless on its own. Discuss weighting etc.

Slide 18

Slide 18

Chess • It is unlikely that Chess will ever be solved, so you cannot know the correct move to make. Checkers was solved in 2007 and has far less moves. • On 11/5/1997, Deep Blue (invented by IBM) beat the then World Champion Garry Kasparov. • Deep Blue was able to compute 200 million positions per second.

Slide 19

Slide 19

Heuristics “Proceeding to a solution by trial and error or by rules that are only loosely defined” Oxford Dictionary

Slide 20

Slide 20

• Heuristics are at the heart of Artificial Intelligence. • An algorithm follows a set of rules. • A heuristic can be used to extend an algorithm by making an educated guess instead of following predefined rules.

Slide 21

Slide 21

University Essays “An essay on the biomedical applications of evolutionary algorithms for image segmentation on MRI scans of the brain” Explain the basics of Evolutionary Algorithms and the type of essays.

Slide 22

Slide 22

University Projects Explain that we can choose our own projects.

Have to persuade supervisors.

Slide 23

Slide 23

Okay, There Are Some Robots

Slide 24

Slide 24

• http://en.wikipedia.org/wiki/File:Alan_Turing_photo.jpg

• http://en.wikipedia.org/wiki/File:Alonzo_Church.jpg

• https://www.youtube.com/watch?v=gJQTFhkhwPA

• www.youtube.com/watch?v=dNRDvLACg5Q

• https://www.youtube.com/watch?v=I9hBeJQUFYg

• https://www.youtube.com/watch?v=aLpaLu2ZVOo

• http://tex.stackexchange.com/questions/132444/diagram-of-an-artificial-neural-network

• http://en.wikipedia.org/wiki/File:Falxmeningeom_MRT_T1_mit_Kontrastmittel.jpg

• http://www.telegraph.co.uk/motoring/news/8876686/Honda-Asimo-robot-advances-in-leaps-and- bounds.html

• https://www.plymouth.ac.uk/schools/school-of-computing-and-mathematics/robot-football

• http://i.dailymail.co.uk/i/pix/2015/02/09/2585F3CF00000578-0-image-a-2_1423524380512.jpg

References