CS 416 Artificial Intelligence

1. CS 416Artificial Intelligence Lecture 2 Introduction

2. CS at UVa • $11M in research grants each year • Top 5% of research is funded by NSF • Faculty trips to NSF set national funding priorities • Free MSFT Visual Studio for all students • 75% faculty growth in past six years • Undergrad research awards from CRA • Highest starting salary (in SEAS) for ugrads

3. Textbook • This is a great book • 2nd edition released three years ago • Most widely used in U.S. universities • It’s so good…. • I’m going to make you read it! • Homework • Read chapters 1 and 2

4. Survey Results • Languages • Supermajority prefers C++ • Three people indicated they’ll need C++ help • LISP? • Math • Many w/o stat • 7 w/o diffyq • 14 w/o linear algebra

5. 5 people w/o GUI experience • 4 people w/o MSFT Windows • 14 people don’t play so many video games • Where have you done the most programming? • 216 – 17 • Graphics – 15 • 201/202 – 6 • OS – 2

6. AI apps • Chess, google, spam filter, finance, chatterbot, games, vacuum • 12% of CPU for AI tasks in games? • More about magic tricks than AI? iRoomba - Rodney Brooks’ (MIT) company

7. Languages • Is AI special in its PL needs? • AI research used to be more symbolic • A language had to make it easy to create symbols and to manipulate them • Some symbols would operate on other symbols • LISP supported “programs as data” and dynamic typing • Modern AI is more quantitative • No language has emerged with an advantage • Our language choice cannot distract from learning AI

8. Languages • C++ - Common industry language • C – gets a little closer to real-time OS • Perl – the duct tape of the Internet – “makes the easy things easy and the hard things impossible” – “there’s more than one way to do it” • Python – “there’s only one way to do it” • Scheme – easy to learn but difficult to extend • Common Lisp – “the programmable programming language” – nontrivial to learn but a decidedly different experience from programming in imperative languages

9. What is expected of you • You’ll have to do math • Neural network update function • Multidimensional function minimization • Probability – Bayes’ Rule • We will teach necessary parts ofstatistics and linear algebra Calculus expected.Probability and Linear Algebra beneficial.

10. What is expected of you • You have to program • The programming assignments are non-trivial • C++ • Requires integration with existing code libraries • Input/output handling (images, for example) • We do not teach programming in this course CS 216 expected.Additional programmingexperience beneficial.

11. This thing • Asimo AI Systems • Thermostat • Tic-Tac-Toe • Your car • Chess • Google • Babblefish

12. Examples • Chess: Deep Junior (IBM) tied Kasparov in 2003 match ATR’s DB Android Ritsumeikan University RHex Hexapod Honda’s Asimo

13. AI Techniques • Rule-based • Fuzzy Logic • Neural Networks • Genetic Algorithms • Exhaustive search • Expert Systems • Logic

14. How to Categorize These Systems • Systems that think like humans • Systems that act like humans • Systems that think rationally • Systems that act rationally

15. Systems that think/act like humans • It’s hard to study things you can’t observe… • How can I know how you think? • Observation is difficult (changing with fMRI). For the most part, you are a “black box” • Cognitive Science • How can I know how you act? • Observation is possible, but hard to control all aspects of experimental conditions. • Turing Test

16. Alan Turing – “Building a Brain” • World War II motivated computer advances • Code breaking (1943, Colossus) – Used to decipher telegrams encrypted using Germany’s encryption machine • Electronic Numerical Integrator and Computer (ENIAC, 1946) • Turing greatly involved with British efforts to build computers and crack codes (Bletchley Park) • Arrested for being a homosexual in 1952 and denied security clearance • Committed suicide in 1954

17. Systems that think/act rationally • Rely on logic itself rather than human to measure correctness • Thinking rationally (logically) • Socrates is a human; All humans are mortal; Socrates is mortal • Logic formulas for synthesizing outcomes • Acting rationally (logically) • Even if method is illogical, the observed behavior must be rational

18. Perspective of this Course • We will investigate the general principles of rational agents • Not restricted to human actions and human environments • Not restricted to human thought • Not confined to only using laws of logic • Anything goes so long as it produces rational behavior

19. What is AI? • The use of computers to solve problems that previously could only be solved by applying human intelligence…. thus something can fit this definition today, but, once we see how the program works and understand the problem, we will not think of it as AI anymore (David Parnas)

20. Foundations - Philosophy • Aristotle (384 B.C.E.) – Author of logical syllogisms • da Vinci (1452) – designed, but didn’t build, first mechanical calculator • Descartes (1596) – can human free will be captured by a machine? Is animal behavior more mechanistic? • Necessary connection between logic and action is discovered

21. Foundations - Mathematics • Leveraging uncertainty (Cardano 1501) • Boolean logic (Boole, 1847) • Analysis of limits to what can be computed • Intractability (1965) – time required to solve problem scales exponentially with the size of problem instance • NP-complete (1971) – Formal classification of problems as intractable

22. Foundations - Economics • Game Theory – study of rational behavior in small games • Operations Research – study of rational behavior in complex systems • Herbert Simon (1916 – 2001) – AI researcher who received Nobel Prize in Economics for showing people accomplish satisficing solutions, those that are good enough

23. Foundations - Neuroscience • How do brains work? • Early studies (1824) relied on injured and abnormal people to understand what parts of brain do • More recent studies use accurate sensors to correlate brain activity to human thought • By monitoring individual neurons, monkeys can now control a computer mouse using thought alone • Melody Moore at GaState – “locked-in syndrome” • (Gordon) Moore’s law states computers will have as many gates as humans have neurons in 2020 • How close are we to having a mechanical brain? • Parallel computation, remapping, interconnections, binary vs. gradient…

24. Foundations - Psychology • Helmholtz and Wundt (1821) – started to make psychology a science by carefully controlling experiments • The brain processes information (1842) • Sense  Think  Act • Cognitive science started at a MIT workshop in 1956 with the publication of three very influential papers

25. Foundations – Control Theory • Machines can modify their behavior in response to the environment (sense / action loop) • Water-flow regulator (250 B.C.E), steam engine governor, thermostat • The theory of stable feedback systems (1894) • Build systems that transition from initialstate to goal state with minimum energy • In 1950, control theory could only describelinear systems and AI largely rose as aresponse to this shortcoming

26. Foundations - Linguistics • Speech demonstrates so much of human intelligence • Analysis of human language reveals thought taking place in ways not understood in other settings • Children can create sentences they have never heard before • Language and thought are believed to be tightly intertwined