Chapter 32. Extraordinary Achievements...Chapter 32. Extraordinary Achievements The Quest for Artificial Intelligence, Nilsson, N. J., 2009. Lecture Notes on Artificial Intelligence,

Chapter 32. Extraordinary Achievements The Quest for Artificial Intelligence, Nilsson, N. J., 2009.

Lecture Notes on Artificial Intelligence, Spring 2012

Summarized by Kim, Kwon-Ill and Yoo, Jun Hee

Biointelligence Laboratory School of Computer Science and Engineering

Seoul National Univertisy

http://bi.snu.ac.kr

Contents 32.1 Games

32.1.1 Chess 32.1.2 Checkers 32.1.3 Other Games

32.2 Robot Systems 32.2.1 Remote Agent in Deep Space 1 32.2.2 Driverless Auto mobiles

2 © 2012, SNU CSE Biointelligence Lab., http://bi.snu.ac.kr

Overview of Chapter 32 32.1 Games

AI applications for playing games Heuristic search & learning

32.2 Robot Systems Automatic control systems

Space ship Automobiles


32.1 Games

Chapter 32. Extraordinary Achievements


32.1 Games Computers is thought by some to be a some what

frivolous diversion from more serious work. Computer game-playing has served as a laboratory for

exploring new AI techniques – especially in heuristic search and in learning.


32.1.1 Chess Deep Blue

In 1997, the world chess champion Garry Kasparov has been defeated by IBM’s “Deep Blue” (2 win/1 lose/ 3 draw).

Deep Blue uses heuristic search. Is this victory can be said “AI achie-

vement”? IBM’s opinion

“No”


Figure 32.1: Garry Kasparov playing chess against Deep Blue in game two of a six-game rematch.

Chess

32.1.1 Chess Differences between Kasparov and Deep Blue

Although “Deep Blue” won, it’s not sort of AI. - IBM


Deep Blue Kasparov Evaluation per second 200,000,000 3

Amount of Chess knowledge

Small Large

Calculation ability Huge Small Used skills Search Tremendous sense

of feeling and intuition

Adaptive Thinking Can’t Very quickly

32.1.2 Checkers “Checkers is Solved”

In September 2007 Jonathan Schaeffer published an article about Checkers game.

It was announcing that “Perfect play by both sides leads to a draw.”

There are 500,995,484,682,338,672,639 different positions in Checkers.

Along the way to the proof, Jonathan’s team developed a checkers program named “CHINOOK.”


Figure 32.2: Jonathan Schaeffer.

Checkers

32.1.3 Other Games Poker

Heads-Up Texas Hold’em (Limit and No Limit). University of Alberta (2008)

Bridge Ginsberg’s Intelligent Bridgeplayer

Go (a.k.a Ba-Duk) One of the hardest game for computers

Scrabble®

Especially suited for computers International Computer Games Association (ICGA)

© 2011, SNU CSE Biointelligence Lab., http://bi.snu.ac.kr 9

32.2 Robot Systems



32.2 Robot Systems Robots are everywhere!

For Mars, deep ocean, volcano Agricultural robots, factory robots, surgical robots, and

warehouse robots More than 30 robotics companies in Pittsburgh

But, it is not intelligent. Remote control by human Improving to autonomous, intelligent action


32.2.1 Remote Agent in Deep Space 1

Deep Space 1(DS1) Oct 24, 1998, NASA

Remote Agent (RA) Robotic system for planning and

executing Ex) “During the next week take

pictures of the following asteroids and thrust 90% of the time

By Jet Propulsion Laboratory Programmed in LISP Works RAX: Space-tested version RA


Figure 32.4: Artist's rendering of DS1 approaching a comet.

Figure 32.6: Illustration of RAX activities.

32.2.2 Driverless Automobiles Very challenging!!

Rapid planning and reaction Wide range of conditions

On sunny and stormy days, at night, on city streets, on high-speed motorways, and on and o desert roads

Crashes In USA, 28,933 people died & 2,221,000 injured in

2007 But, this numbers mean only 1 person killed per

100 million vehicle miles traveled!!


32.2.2 Driverless Automobiles DARPA’s Grand Challenge in 2004

Auto-drive on-and-off road in the desert ALVINN, RALPH, and Navlab by CMU

All failed

DARPA’s Grand Challenge in 2005 5 team completed the course!! Computer vision technology


Figure 32.7: Stanley on Beer Bottle Pass followed by a DARPA chase vehicle.

Figure 32.8: Sandstorm on Beer Bottle Pass.

32.2.2 Driverless Automobiles DARPA’s Urban Challenge in 2007

60 mile course in a mock city environment 6 team completed successfully!!

Future of Driverless Automobiles “By 2030, half of our highway miles will be driven

autonomously without human input.” by S. Thrun Various societal and legal problems Automated aids to human drivers in a few years


Figure 32.10: Tartan Racing team leader William (Red) Whittaker and Boss pose

with first place trophy.

Summary 32.1 Games

Chess Checkers Other Games

32.2 Robot Systems Remote Agent in Deep Space 1 Driverless Auto mobiles


Appendix



32.1.1 Chess IBM’s opinion

Deep Blue uses “brute-force” methods. Deep Blue could draw on standard moves over 4,000

positions and also be influenced by a 700,000 grand master game database.

No formula exists for intuition.


32.1.1 Chess In broader view of A.I. – another view

Although Deep Blue relied mainly on brute-force methods (rather than on rule-based reasoning), it use heuristic search (one of foundational techniques of AI).

In 2006

World Chess Champion Vladimir Kramnik vs. Deep Fritz Deep Fritz (version 8) won 2 games and 4 draws.

The latest version of Deep Fritz is 11.


32.1.2 Checkers


32.1.2 Checkers The Proof

Axis y: the number of rest pieces.

Axis x: the logarithm of the number of positions.

Shaded area: less than 10 pieces left (39,271,258,813,439 positions)

Optimum play involves using heuristic search to find a line of play guaranteed to get shaded area.


Figure 32.3: Schematic for the checkers proof.

32.1.2 Checkers vs. Human

In 1992, Checkers champion Marion Tinsley beat CHINOOK four wins to two, with thirty-three draws.

Rematch has been held in 1994, CHINOOK was declared the Man-Machine World Champion because of Tinsley’s resign, citing health reasons.


Figure 32.2: Jonathan Schaeffer.

Checkers

32.1.3 Other Games Poker

Heads-Up Texas Hold’em (Limit and No Limit). University of Alberta (2008)

http://poker.cs.ualberta.ca Devoted to the AAAI Computer Poker Competition.


Royal straight flush

http://poker.cs.ualberta.ca/

32.1.3 Other Games Bridge

Goren in a Box (a.k.a Ginsberg’s Intelligent Bridgeplayer) Matt Ginsberg

Uses Monte Carlo approach.

http://www.gibware.com


Bridge play table

http://www.gibware.com/

32.1.3 Other Games Go (a.k.a Ba-Duk)

MoGo Titan (2008) INRIA France and Maastricht University in the Netherlands. Beat a professional Ba-Duk player in a game with the Dutch

supercomputer Huygens. This was given a handicap of nine stones.

Ba-Duk is probably one of the hardest game for computers. Human vs. Computer Go games:

http://www.computer-go.info/h-c/index.html


Ba-Duk table

http://www.computer-go.info/h-c/index.html

32.1.3 Other Games Scrabble®

Especially suited for computers with their abilities to access large dictionaries and conduct massive searches.

Scrabble programs now routinely beat expert humans. Brian Sheppard, “World-Championship-Caliber Scrabble,"

Artificial Intelligence, Vol. 134, Nos. 1-2, pp. 241-275, January 2002.

26 © 2012, SNU CSE Biointelligence Lab., http://bi.snu.ac.kr Scrabble board

32.1.3 Other Games International Computer Games Association (ICGA)

Information about all kinds of computer game-playing tournaments. http://www.icga.org/

27 © 2012, SNU CSE Biointelligence Lab., http://bi.snu.ac.kr Homepage of ICGA

http://www.icga.org/

32.2.1 Remote Agent in Deep Space 1

Subsystems of RA Planner/Scheduler (PS) Mission Manager (MM) Smart Executive (EXEC) Mode ID system

Procedure Given mission goal & spacecraft state MM formulates a planning problem for PS PS construct a plan (schedule of actions) for EXEC

Planning Experts participate in planning EXEC decompose high-level schedule to commands for Real-Time

Execution For failed tasks, EXEC attempt alternatives or Mode ID and Recovery

system analyze & repair the problem …


Figure 32.5: Remote agent architecture.

32.2.2 Driverless Automobiles Brief history

ALV project of the Strategic Computing Program in the mid-1980s by DARPA

ALVINN, RALPH, and Navlab by CMU VaMP by E. Dickmanns at Universit�at der Bundeswehr

in Munich Drive from Munich to Odense, Denmark, and back in

1995 Computer vision and radar

Tsukuba Mechanical Engineering Lab in Japan 2getthere in Netherlands ARGO Project in Italy



Auto-drive on-and-off road in the desert For unmanned aircrafts & vehicles for army

142-mile in 10 hours 2000 “waypoints”, navigating around obstacles, staying on

roads, avoiding drop-offs, … GPS system

$1 million prize All failed

Farthest travel : 7.5 mile Some vehicles, good at following way points, are poor at

avoiding obstacles, and vice versa.



5 team completed the course!! 1st: Stanley from Stanford University

Used ranging and optical sensors Computer vision technology


Figure 32.7: Stanley on Beer Bottle Pass followed by a DARPA chase vehicle.

Figure 32.8: Sandstorm on Beer Bottle Pass.

32.2.2 Driverless Automobiles Technologies in Stanley, the winner of GC2005

Sebastian Thrun, Michael Montemerlo System

Six-processor computing platform (Intel) Drive-by-wire control system Sensors

5 laser range-finding units, 1 video camera, GPS system, Gyroscope, Accelerometers

Probabilistic terrain analysis (PTA) Distinguish drivable / nondrivable terrain

Computer vision Drivable surface identification with surface patches

Online speed control Trade off risk and speed


Figure 32.9: Sebastian Thrun (left) and Michael Montemerlo (right).

32.2.2 Driverless Automobiles DARPA’s Urban Challenge in 2007

Visiting check points in 6 hours 60 mile course in a mock city environment

Merging, passing, parking, negotiating intersections, …

California driving regulations Traffic: 50 vehicles simultaneously

89 applicants → 11 teams for final 6 team completed successfully!!

1st: Boss from CMU


Figure 32.10: Tartan Racing team leader William (Red) Whittaker and Boss pose

with first place trophy.

32.2.2 Driverless Automobiles Technical issues in Urban Challenge

Follow rules of the road Detect and track other vehicles at long ranges Find a spot and park in a parking lot Obey intersection precedence rules Follow vehicles at a safe distance React to dynamic conditions such as blocked roads or

broken-down vehicles …

Competitions sponsored by companies Volkswagen in 2007 GM in 2008


32.2.2 Driverless Automobiles Future of Driverless Automobiles

“By 2030, half of our highway miles will be driven autonomously without human input.” by S. Thrun

Various societal and legal problems Accident liability Human desire to be in control …

Automated aids to human drivers in a few years All-around collision warning systems Radar-based cruise control Lane-change warning devices Electronic stability control GPS & digital maps


Documents

Chapter 32. Extraordinary Achievements...Chapter 32. Extraordinary Achievements The Quest for Artificial Intelligence, Nilsson, N. J., 2009. Lecture Notes on Artificial Intelligence,