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So there's already a Doom interface to killing UNIX processes:
What i'm thinking of is an abstracted set of library calls that will take
a complex "work problem," generate a corresponding "game problem" (like
the next block shape in Tetris), and use
the solution the player provides
to solve the "work problem." The crux that i haven't solved is this: are
there formulae that can produce a net savings of work by mapping the
work-actions to game-actions (and back), over just solving the original
If not, maybe we could just collect entropy from Internet-connected gamers to improve rand().
ps. I did read _Ender's Game_. It reminded me of Netrek.
"Sokoban is PSPACE-complete" [johan, Mar 03 2000, last modified Oct 21 2004]
SOKOBAN and other motion planing problems [johan, Mar 03 2000, last modified Oct 21 2004]
The "minesweeper consistency problem" is NP-complete. [egnor, Mar 03 2000, last modified Oct 21 2004]
||What do you think you're doing when you
play Solitaire on a Windows machine, merely
wasting time? Certainly not. A mapping has been made
between the intricacies of Klondike and various
well-understood software engineering practices.
||Once the process has been bootstrapped, you need never employ
costly software engineers and testers again. The users generate the
||There's some mathematical work on the
computational complexity of various
games. Some have been shown to be
P-, NP- and even PSPACE- complete.
(IIRC, Shokoban is PSPACE-complete.)
Not only _could_ we map any problem in
those complexity classes into those
games, at least in some cases the
mapping is already published.
||That's a good point. I like my work (UNIX sysadmining) but i like playing games, and i know a lot of people who would rather be playing games than doing anything else. This would be a way all that crainiating that goes forth into computer gaming could be doing "real" work, and perhaps someone could make a living playing games, just like all those sports stars..