Games and Aesthetics:
Play beyond Zero Sums

Ingo Althöfer, September 2011 and February 2013


Think of your pet game. A computer program for this game does not automatically mean a big step towards happiness. Often, the bot is much too strong - so you will lose against it all the time. Or, the bot may be far too weak to be an appropriate playing partner.

In such a situation (I have several pet games ...), at one moment back in 2002 I started not to play for a win any longer, but for beauty. Two different cases.
Either: When I am clearly ahead, I still want to win, but I also try to achieve a nice final position.
Or: When my situation in a game is hopeless, it becomes my only goal to reach a nice final position, regardless if this will make the loss even more dramatic.
Of course, here "beautiful" and "nice" are subjectively "defined" by my own preferences and feelings - which may change from day to day, or even from moment to moment ...

In the first part of this exhibition you find screenshots on some nice board filling games, for which I own computer programs. The second part shows shows pictures of nice (final) positions for normal (i.e. "hands on") games. The textlines below some of the pictures can be clicked to get more explanations.




Square_Down
The "Zillions-of-Games" program for this game by Karl Scherer is way too strong for me.





Py
In all symmetric settings this program is so weak that I win almost without any thinking.




Grey Level Py




Documenta
Within "Zillions-of Games 1", Documenta is played really poorly by the bot. For me it was a very easy exercise to win against it and to generate nice end positions on the board. In contrast, the newer version Zillions-2 is an opponent at eye-level.



Monte-Carlo Go

Starting in 2007, bots based on Monte Carlo evaluations dominate the compute go scene. One of their astonishing properties - besides the impressive playing strength (some of them have reached dan-level strength on standard hardware) - is the willingness to be happy with a win by 0.5 points, even if they had a trememdous advantage during the game.
This is an ideal starting point for "Picture Go": Allow the bot to gain a clear lead, and as compensation, get the freedom to "design" a pixel picture of your choice on the board.



Picture Go with Many Faces




Crazy Stone is a self-willed "Monte-Carlo beast".
It seems to be willing to go for more than only a minimal winning margin. A cross was my goal - the outcome is not fully satisfying.



Leela too,
especially on the monstrous 37x37-board. Tenuki works differently!





For the European Go Congress 2012, Tanja Esser had designed two wonderful ink paintings. I was so lucky to acquire them. Thanks to Mrs. Esser for allowing me to show the pictures online!

The subtitles are mine. The go stones in the vertebral column are symbolising the "instinctive" or "reflex-like" character of Monte Carlo algorithms. In contrast, in human go the stones have their places in the brain.



From the old days of Computer Go



Old Picture Go
That the left one would or should become an elephant became clear to me only step by step during the game. Chen Zhixing, the author of Handtalk, exclaimed immediately "oh, an elephant", when I showed him the final position.




Games for Hands on




Palago by Cameron Browne.




Zoff der Zünfte
The yellow figures are Thorsten Sillke's "Meisterklasse".




Carcassonne ...
... is the permanent bestseller of Klaus Wrede. It was "Game of the Year" in Germany in 2001. Many people play it mainly because of the nice landscapes.




Blitz




Almost like by Escher:
How is the staircase running? Material is from the game Torres.




Opaque Stones - for free play without any formal rules.

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