Random GoRandom Go                                    1. Many games become boring                                    2. Ra...
Many games become boring whenthey are too much studiedThis part for some preliminaries:1. Go starts from an empty board (u...
1. Go starts from an emptyboardAn interesting book on the philosophy of Go: K. Chairasmisak, “Teachings by an Asian Leader...
1. Go starts from an emptyboard (usually)Tibetan Go   Sunjang Baduk Go   Batoo: 3 stones / player                         ...
2. Computers still far from pros Go can be played on various board sizes. 9x9         13x13               19x19           ...
2. Computers still far from pros Go can be played on various board sizes. In 9x9, computers and humans are close. In 13x13...
3. Openings are boringEntire books on openings.Fuseki / Joseki:Fuseki: full board openingJoseki: local opening (does not s...
Random GoRandom Go                           1. Many games become boring                     2. Randomization brings some ...
The case of chess  Plenty of complicated openings are known    - We can become strong by rote learning ?    - Is it so gre...
960                                   Chess3 examples of initial situations10
Chess 960: conclusion ? Strength in Chess960 correlated (but no equal to) strength in Chess No more boring opening phase N...
Random GoRandom Go                           1. Many games become boring                       2. Randomization brings som...
Computers in Go + Random Go                                    (IEEE SSCI 2011)The computer                            The...
Computers vs Humans instandard Go  Some nice successes in computer-Go  Wins against pros in 9x9  Wins with handicap 6 agai...
Computers in random-GoRandomly put 180 stones on the boardCan be unfairSo: Randomly put       180 stones Check if   equili...
Computers vs Humans inrandom Go<= 160 random stones: human wins everything.240 random stones:  Human chooses black  Comput...
On which situations arecomputers weaker than humans ?           ( 17
The game of Go is a part of AI. Consider ridiculous in front of children.Computers are              a situation with plent...
The game of Go is a part of AI. Consider ridiculous in front of children.Computers are              a situation with plent...
The computer stupidly analyzes allsymmetries of all strategies.                              800 cores, 4.7 GHz,          ...
The game of Go is a part of AI.Computers are ridiculous in front of children.                                             ...
On which situations arecomputers weaker than humans ? Are there less situations                           )  with plenty o...
ConclusionsComputers much stronger from random initial boards.More fun for humans (see tests in European Go Congress 2011)...
Finished!            24
Upcoming SlideShare
Loading in...5
×

Random Go

246

Published on

Wins against strong humans in the game of Go with random initial positions


@inproceedings{helmstetter:inria-00625815,
hal_id = {inria-00625815},
url = {http://hal.inria.fr/inria-00625815},
title = {{Random positions in Go}},
author = {Helmstetter, Benard and Lee, Chang-Shing and Teytaud, Fabien and Teytaud, Olivier and Mei-Hui, Wang and Yen, Shi-Jim},
abstract = {{It is known that in chess, random positions are harder to memorize for humans. We here reproduce these experiments in the Asian game of Go, in which computers are much weaker than humans. We survey families of positions, discussing the relative strength of humans and computers, and then experiment random positions. The result is that computers are at the best amateur level for random positions. We also provide a protocol for generating interesting random positions (avoiding unfair situations).}},
language = {Anglais},
affiliation = {Laboratoire d' Informatique Avanc{\'e}e de Saint- Denis - LIASD , Department of Computer Science and Information Engineering - CSIE , Laboratoire de Recherche en Informatique - LRI , TAO - INRIA Saclay - Ile de France , National Dong Hwa University - NDHU},
booktitle = {{Computational Intelligence and Games}},
address = {Seoul, Cor{\'e}e, R{\'e}publique Populaire D{\'e}mocratique De},
audience = {internationale },
year = {2011},
month = Sep,
pdf = {http://hal.inria.fr/inria-00625815/PDF/randomgo.pdf},
}

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total Views
246
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
Downloads
5
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Random Go

  1. 1. Random GoRandom Go 1. Many games become boring 2. Randomization brings some fun 3. But computers are terrible in random gamesTAO, Inria-Saclay IDF, Cnrs 8623, Lri, Univ. Paris-Sud,OASE Lab,Korea,Summer 2011 1
  2. 2. Many games become boring whenthey are too much studiedThis part for some preliminaries:1. Go starts from an empty board (usually)2. Computers are still far from pros in Go3. Openings are complicated, known, boring (I know many of you dont agree). 2
  3. 3. 1. Go starts from an emptyboardAn interesting book on the philosophy of Go: K. Chairasmisak, “Teachings by an Asian Leader”(English title by me; exists in French & in Chinese at Least), 2005. (Thailand CEO of 7-Eleven)Go has both tactical elements and a strategyStarting from the empty board is very special==> link between both ?==> something specifically human in games starting from the empty board ? 3
  4. 4. 1. Go starts from an emptyboard (usually)Tibetan Go Sunjang Baduk Go Batoo: 3 stones / player (anywhere) (maybe value of the game close to 0.5 ? whereas 0 or 1 for Go)===> 3 exceptions; yet, nearly empty===> and many people study Tsumegos (not empty board!) 4
  5. 5. 2. Computers still far from pros Go can be played on various board sizes. 9x9 13x13 19x19 5
  6. 6. 2. Computers still far from pros Go can be played on various board sizes. In 9x9, computers and humans are close. In 13x13, computers are still weaker than humans. H1.5. In 19x19 Go, computers are still very weak compared to pros. H6 is a minimum. 6
  7. 7. 3. Openings are boringEntire books on openings.Fuseki / Joseki:Fuseki: full board openingJoseki: local opening (does not say in which part of the board you should play)Less restrictive than in Chess.Yet, you might have to study a lot if you want to reach the top level. 7
  8. 8. Random GoRandom Go 1. Many games become boring 2. Randomization brings some fun 3. But computers are terrible in random games 8
  9. 9. The case of chess Plenty of complicated openings are known - We can become strong by rote learning ? - Is it so great as a pedagogical tool ? It makes the game a bit boring Too easy for white to force a draw Fischer proposed randomization: Fischer Random Chess (also known as Chess 960) Principle: White pieces randomly drawn (within some constraints) Black pieces in symmetry 9
  10. 10. 960 Chess3 examples of initial situations10
  11. 11. Chess 960: conclusion ? Strength in Chess960 correlated (but no equal to) strength in Chess No more boring opening phase Not many human/computer comparisons ==> well do it in Go Algorithm carefully designed by Fischer for making the game somehow equilibrated ==> leads to a restricted number of initial situations (960) ==> well do this automatically (→ much more initial positions) 11
  12. 12. Random GoRandom Go 1. Many games become boring 2. Randomization brings some fun 3. But computers are terrible in random games 12
  13. 13. Computers in Go + Random Go (IEEE SSCI 2011)The computer The humanDell Poweredge R900 One big brain.16 cores, 2.96 GHz, 64bits Ranked fourth in World Amateur Championship 2004. Former French champion. Knows computers. 13
  14. 14. Computers vs Humans instandard Go Some nice successes in computer-Go Wins against pros in 9x9 Wins with handicap 6 against pros in 19x19 Yet, the human wins easily with handicap 6. ==> computer crushed 14
  15. 15. Computers in random-GoRandomly put 180 stones on the boardCan be unfairSo: Randomly put 180 stones Check if equilibrated by playing multiple games If not, restart. Human chooses his color. 15
  16. 16. Computers vs Humans inrandom Go<= 160 random stones: human wins everything.240 random stones: Human chooses black Computer wins as white Human wins as white ==> maybe unfair ?180 random stones: First position: computer wins both as black and white Second position: computer looses one game.Remarks: Many games the same day ==> human tired Nonetheless, such results16impossible in standard Go
  17. 17. On which situations arecomputers weaker than humans ? ( 17
  18. 18. The game of Go is a part of AI. Consider ridiculous in front of children.Computers are a situation with plenty of equivalent strategies. Easy situation. Termed “semeai”. Requires a little bit of abstraction. Random Go Korea 18
  19. 19. The game of Go is a part of AI. Consider ridiculous in front of children.Computers are a situation with plenty of equivalent strategies. Easy situation. Termed “semeai”. Requires a little bit of abstraction. All orders for filling these locations are equivalent. All orders for filling these locations are equivalent. Random Go Korea 19
  20. 20. The computer stupidly analyzes allsymmetries of all strategies. 800 cores, 4.7 GHz, top level program. Plays a stupid move.Random Go Korea 20
  21. 21. The game of Go is a part of AI.Computers are ridiculous in front of children. 8 years old; little training; finds the good move Random Go Korea 21
  22. 22. On which situations arecomputers weaker than humans ? Are there less situations ) with plenty of invariances in random-Go ? Less sophisticated interactions between various areas of the board ? 22
  23. 23. ConclusionsComputers much stronger from random initial boards.More fun for humans (see tests in European Go Congress 2011)New results (not in the paper): tests against “not so strong” humans.Pedagogy: - It is often said that Go, Chess, … are good pedagogical tools (true ?). - But rote learning is important in such games - Random games a good solution ? (questionable... less human-specific ?)Computational point of view: We could not generated positions with many many random stones ==> rejection rate almost 100% ==> How to improve this ? ==> In terms of Go, maybe a good Ishi-No-Shita-generator.Beyond games: Generate test cases (for other pbs) with similar approaches ? Link with testing of some abilities (who plays randomGo well ?) 23
  24. 24. Finished! 24
  1. A particular slide catching your eye?

    Clipping is a handy way to collect important slides you want to go back to later.

×