1. D Goforth - COSC 4117, fall 20061 Notes  Program evaluation – Sept 11-12 Student submissions  Mon. Sept 11, 4-5PM  FA 181 Comments to committee are anonymous  Wine and cheese – Sept 15, 1:30-4:00PM

2. COSC 4117 Artificial Intelligence Thinking and acting at least as well as humanly possible http://www.cs.laurentian.ca/dgoforth/cosc4117/outline.html

3. D Goforth - COSC 4117, fall 20063 Course outline  Russell and Norvig – ch 1-12 plus handouts  Major programming project50%  3 assignments24%  Final exam 26%

4. D Goforth - COSC 4117, fall 20064 Artificial intelligence  what an ‘electronic brain’ does…  methods for solving (partially) problems that are difficult because known algorithms are O(e n )  play chess no algorithms are known  converse in English we hardly know where to begin  fall in love

5. D Goforth - COSC 4117, fall 20065 Definitions of AI  think like a human being  think like a human but better  act like human being – Turing test  be a successful functioning entity

6. D Goforth - COSC 4117, fall 20066 Definitions of AI – human thinking  think like a human being based on philosophy, psychology, neuroscience,... programs to emulate human processes: learning, reasoning, memory testing theories of how humans think influence on models of human thinking weak and strong AI – mind-body problem – Searle’s Chinese room thought experiment

7. D Goforth - COSC 4117, fall 20067 Definitions of AI – think rationally  think like a human but better battle of neats and scruffies extension of long tradition of analysing thought – rationality logic as basis for programming – completed by 1960’s BUT limited usefulness extensions to real situations: too little, too much or inconsistent information

8. D Goforth - COSC 4117, fall 20068 Definitions of AI – act human  act like a human being bird-flight argument ‘black box’ emulation – Turing test intelligence/thinking plus the ‘hard’ peripherals: perception, language, motion

9. D Goforth - COSC 4117, fall 20069 Definitions of AI – act rationally  be a successful functioning entity as ‘agent’ in an ‘environment’ set goals perceive environment communicate with other agents plan act  object-oriented model, subsumes all others  current best definition of AI

10. D Goforth - COSC 4117, fall 200610 50 th anniversary Dartmouth Conference 1956  McCarthy coined “Artificial Intelligence”  Slogan that was starting point of discussion: “Every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.”  Newell & Simon: Logic Theorist first noncalculating program – abstract proofs

11. D Goforth - COSC 4117, fall 200611 History of AI - 1  ‘electronic brain’ – potential of logic circuitry for automated reasoning  Minski - neuron models of processing – father of scruffies – “Society of Mind”  Newell & Simon - symbol processing – in contrast to ‘computing’ ( == number crunching)  McCarthy – neat freak – computing environments (LISP, time-sharing)

12. D Goforth - COSC 4117, fall 200612 History of AI - 2  progress fast; predictions faster systems demo-ing capabilities in reasoning, planning, robotics control conversation logics extended to uncertain knowledge, assumptions, viewpoints  crash of 1970’s ‘scaling up’ – exponential performance ‘brittleness’ – importance of knowledge failure of neural network ‘perceptrons’

13. D Goforth - COSC 4117, fall 200613 History of AI - 3  knowledge-based systems encoding experience and expertise rules and heuristics  meta-knowledge – knowing how to know – ontology (semantic net)  common sense  triumph of the meta-neats – Cohen’s analysis, formalizing the science of AI

14. D Goforth - COSC 4117, fall 200614 History of AI - 4  the agent model – Newell  influence of Russell and Norvig  apparent future directions: autonomy in bigger and bigger environments *bots of all kinds internet as environment – applications  search engines, language translation,...

15. D Goforth - COSC 4117, fall 200615 History of AI - 5  1997 Chess champion IBM Deep Blue  2005 DARPA Grand challenge Sebastian Thrun’s Stanley ‘On Saturday, the Stanford Racing Team's robotic car, "Stanley," drove autonomously across 131.6 miles in the Mojave Desert in six hours and 53 minutes, finishing about 11 minutes faster than Carnegie Mellon's "Sandstorm." Its average speed was 19.1 mph, versus Sandstorm's 18.6 mph.’ cnet news, Oct 9, 2005 (news.com.com)

16. D Goforth - COSC 4117, fall 200616 The programming project  intelligent game player agent to act autonomously in game environment perceptions and actions are easy goal setting is easy evaluation of performance is easy focus is on core intelligence: playing well; not easy

17. D Goforth - COSC 4117, fall 200617 The programming project  stages: 1.pick teams and design game structure 2.program the game 3.program agent to play game 4.compete against other agents 5.write up the results  work in teams of 1 or 2

18. D Goforth - COSC 4117, fall 200618 The programming project  this year’s game is KING’S COURT  first deadline: Monday, Sept 25 pick a team design data structure for the game