Games as a Test Bed for Developing AI Applications (in Physics) Brains vs Computers Symposium of the “van der Waals” study association December 10, 2013 Jos Uiterwijk Department of Knowledge Engineering Maastricht University 1/36

Computer chess and computer games The role of computer games in Artificial Intelligence Brute force? The impact of knowledge and heuristics New developments AI and Physics Conclusions Jos Uiterwijk Overview 2/36

Jos Uiterwijk Some history Start of computer chess The Turk It was all fake! 3/36

Jos Uiterwijk Origin of the AI Starts around 1950 Chess as the drosophila melanogaster of AI 2 pioneers: –Alan Turing –Claude Shannon 4/36

1.Rules are simple, but the strategy is complex 2.Domain is fixed, by which programs are easily comparable, both with other programs and with humans. By the nature of a game it is easy to test if a new technique is “better”. 3.Games are typical for human intelligence (Goethe: chess is the touchstone of the intellect). This explains the interest from psychology. Jos Uiterwijk Why is chess of interest for AI? 5/36

Jos Uiterwijk Alan Turing ( ) Worked in Bletchley Park during World War II Decoding the German Enigma codes: The Bombe Was the first who seriously posed the question: Can machines think? 6/36

Jos Uiterwijk Alan Turing: Turing test 7/36

Used the computer in his “spare time” for chess programming. Was the first who wrote a chess program Jos Uiterwijk Alan Turing 8/36

Jos Uiterwijk Claude Shannon ( ) Was also concerned with computer chess Built chess endgame machines Wrote the “bible” of chess programming: Programming a computer for playing chess (1950) 9/36

Jos Uiterwijk Claude Shannon Shannon was brilliant in many domains, both theoretically and practically: he built among others a juggling robot By the way, he also could juggle himself quite good! 10/36

Jos Uiterwijk State of the Art in computer chess Nowaday computers are stronger than human world champions Mile stone: Kasparov losing from chess machine Deep Blue in 1997 Kramnik loses from the “simple” desk top program Deep Fritz in /36

Jos Uiterwijk Adriaan de Groot ( ) Professor in psychology Studies on “chess thinking” PhD thesis (1946) Het Denken van den Schaker, translated (1965) as Thought and Choice in Chess 12/36

For many board games just used brute computer power was initially used (i.e., as many calculations as possible): dumb but fast. This is called the brute-force approach Later the question arose: can the brain still beat the machine by clever use of knowledge? The knowledge-based approach Jos Uiterwijk Brute force 13/36

Facts Heuristics (rules of thumb) Jos Uiterwijk Knowledge 14/36

The “mutilated chess board” problems: Can I put domino stones (of 2 x 1 size) in such a way on the board that all squares are covered? Jos Uiterwijk Facts (1) ? ? The 4x4 problem 15/36

The 8x8 problem Jos Uiterwijk Facts (2) 16/36

The 20x20 problem Jos Uiterwijk Facts (3) 17/36

The knight jump puzzle: Can you find a route on the chess board starting at a given location such that all squares are traveled exactly once? Heuristic (rule of thumb): First visit the corners, then the edges, etc., gradually going to the centre Does this heuristic work? Jos Uiterwijk Heuristics (1) 18/36

The knight jump puzzle on the 8x8 board Jos Uiterwijk Heuristics (2) 19/36

However: a heuristic is fallible: The 5x5 knight jump puzzle Jos Uiterwijk Heuristics (3) 20/36

Another knight jump problem Jos Uiterwijk Chosing the right representation What is the shortest route to switch the white and black knights? start goal 21/36

Step 1: number the squares: Jos Uiterwijk Solution 22/36

Step 2: draw the neighbour diagram for knight jumps (which squares are reachable in one jump?) Jos Uiterwijk from: we get: 23/36

Step 3: Jos Uiterwijk and the goal situation Draw the start situation 24/36

Step 4: Recognise that this is just a railcar switching problem! Jos Uiterwijk 25/36

Step 5: solution now is simple: Jos Uiterwijk 12 steps 14 steps 6 steps 8 steps ===== 40 steps 26/36

Many other games have been or are target of AI research. Many have been solved, which means that the computer has an optimal strategy against any resistance. Others are played above human level Some are still difficult Jos Uiterwijk State of the art for other computer games 27/36

Until recently, strong humans refused to play against computers Reason: computers are too strong (recently the human world champion nevertheless played a match; he lost 8-0!) Jos Uiterwijk Reversi 28/36

Standard boards are completely solved The Checkers program CHINOOK even gained the official World Champion title Jos Uiterwijk Connect-Four, Domineering, Checkers 29/36

Until recently, strong humans refused to play against computers. Reason: humans are too strong! This is, since 10 years, rapidly changing though (Monte Carlo simulations work great!) Jos Uiterwijk Go 30/36

Much progress on: –Games with chance (Poker, Backgammon) –Multi-player games (Chinese checkers) –Imperfect-information games (Bridge) –Real-time strategy (RTS) games Jos Uiterwijk And many other games... 31/36

Just mentioning some physics domain: –Nuclear physics (safety!) –Medical physics (data analysis; data mining) –Robotics (large progress) –Vision (still difficult) –Intelligent design –Many kinds of simulations, from microscopic small to astronomic large Jos Uiterwijk Applications in Physics 32/36

They all benefit from computer science and AI in particular, such as: –Fast calculations –Machine learning –Pattern recognition / data mining Jos Uiterwijk 33/36

Chess (and other games) –Drosophila melanogaster of AI –Tool for development of new techniques –Insight into human intelligence Computers can play many (board) games at (supra) expert level Other games are still a challenge (Go). Jos Uiterwijk Conclusions 34/36

Can and will computers beat the human brain? –Yes, in many complex (but otherwise dumb) domains –No, in several not so complex, but intelligent, domains, for a long time to go! –Much game research has to be done! Jos Uiterwijk 35/36

Jos Uiterwijk The End! 36/36