1. What is AI…? Dr. Simon Colton Computational Bioinformatics Laboratory Department of Computing Imperial College, London

2. What isn’t Artificial Intelligence AI in PopSci books and the Media Kevin “March of the Machines” Warwick –Robots will take over the Earth Roger “Emperors New Mind” Penrose –Computers will never be intelligent

3. What isn’t AI Mark “The Human Computer” Jeffery –Computers will evolve to be human Ray “ The Age of Spiritual Machines ” Kurzweil –Humans will evolve to be computers ?

4. Two Restricted Views of AI As a tool to study (human) intelligence –Just the latest part of the philosophers toolbox –Mostly scientific As a set of methods for solving problems –Which take intelligence to solve in humans –Mostly technological In reality, AI encompasses both of these –Part science, part technology

5. Two Characterisations of AI “What problem do I have?” “How on earth can I get my machine to do clever things?”

6. Characterisation by Problem If you know the type of problem –There are established techniques to use Some problems you may want solving: –Translating, proving, learning, optimising, … –Seeing, hearing, speaking, moving, … This is how AI is usually taught –And how subjects are arranged in textbooks

7. Considerations for Problem Solving How to specify the problem –So the computer knows when it’s done How to represent solutions –Representation, representation, representation –Symbolic and non-symbolic How to search for solutions –Calculation, simple search, rules of thumb

8. An Example: Computer Maths Would you do this by hand if you had a calculator: 171717 * 98765? –If we can get a computer to do it, Then it’s extremely reliable Computers do more complicated maths: e.g., 17 < x < 19, 15 < x+y < 20, 13 < y-x < 17 And can beat humans sometimes: –I wanted to prove, that, in ring theory: (all x, (x+x = x*x))  (all w x (((w*w)*x)*(w*w)) = id) –I couldn’t prove this, but Otter could!

9. A Nicer Characterisation As answers to: –“How can I get my machine to be clever” Seven answers over the years: –Use logic –Use introspection –Use brains –Use evolution –Use the physical world –Use society –Use ridiculously fast computers

10. Elementary, my dear Watson Logical approach –Idea: represent and reason “It’s how we wish we solved problems… –Just like Sherlock” Very well respected –Established 3000 years of development –Techniques for reasoning Deduction & induction –Programming languages

11. Introspection Logic has limits –Combinatorial explosion “Maybe we’re not logical –But we are intelligent” Use introspection –Can be highly effective –Can be problematic Heuristic search –Using rules of thumb to guide the solving process

12. BrainWare “Maybe we don’t know our psychology –But it’s our brains which do the intelligent stuff” And we do know –Some neuroscience Idea is to build: –Artificial Neural Networks –Simulate neurons firing Networks configuring themselves Mostly used for prediction –E.g., stock markets (badly)

13. Evolve or Perish “Our brains give us our smarts, –But what gave us our brains?” Idea: evolve programs –Simulate reproduction and survival of fittest Problem Solving: –Genetic algorithms (parameters) –Genetic programming (program) Artificial Life –Can we evolve “living” things

14. The More the Merrier “We live and work in societies –Each of us has a job to do” Idea to simulate society –Autonomous agents Each has a subtask –Together solve the problem Agencies have structure Agents can –compete, co-operate, haggle, argue, …

15. The Harsh Realities of Life “But we evolved intelligence for a reason” Idea: get robots to do simple things in the physical world –Dynamic & dangerous From survival abilities –Intelligence will evolve Standing up is much more intelligent than –Translating French to German –In Evolutionary terms

16. Brute Force “Let’s stop being so clever and use computers to their full” –Processor/memory gains have been enormous Can solve problems in “stupid” ways –Relying on brute force The Deep Blue way –Little harsh on IBM

17. An Example: RHINO Robotic museum tour guide –Robot + computers –And worried researchers Who didn’t intervene Highly successful –18.6 kilometres, 47 hours –50% attendance rise –1 tiny mistake No breakage/injury Great science –Using many approaches –Won best paper award

18. Where is AI? In industry – see Rob’s talk In education – see Andrew’s talk In research –Computing, psychology, philosophy, –Cognitive science, linguistics, biology, –Mathematics, physics, … Artificial Intelligence does not class itself as simply a subset of computing

19. Some Aspirations “Big” AI –Building of human-level intelligence into robots like Lieutenant Commander Data “Small” AI –Get computers to undertake some intelligent tasks –Mostly problem solving –But sometime more creative “artefact generation” Painting pictures, composing melodies, writing poems, … –This is what most of us do

20. Computers can Create Produced by the NeVar system © Machedo Uses Genetic Programming Evolve the program to draw these Evolutionary Art is very big

21. Resources… This is meant to stimulate questions