an ai game. maybe.
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ai
appengine
lib
maps
media
test
.gitignore
README.md
ai_exceptions.py
app.yaml
appengine_config.py
cli.py
code_signature.py
cron.yaml
gui.py
main.py
mapobject.py
ncurses_gui.py
settings.py
tournament.py
tuct.py
unit.py
world.py
worldmap.py
worldtalker.py

README.md

DMANGAME

Website

check the dmangame page for more information.

Download

You can find the latest version of the source code on github

Dependencies

Required:

python 2.x

Optional:

If using graphics, pygtk (which should include cairo).

If posting to app engine, pyyaml

Playing

# Play with graphics
python main.py ai/captureai.py ai/killncapture.py

# Play without graphics and a web replay. Open output.html to view the game replay.
# NOTE: This file is a massive JSON crusty file. If you want to copy it
# somewhere, make sure to compress it (scp -C) or gzip it first.
python main.py ai/captureai.py ai/killncapture.py -c -o output.html

# Use NCURSES GUI (Game output gets saved to game.log and game.out)
python main.py ai/captureai.py ai/killncapture.py -cn

# Play on a specific map
python main.py ai/captureai.py ai/killncapture.py -m maps/micro.py

# Show AI debug highlighting for AIs.
# Note: Each AI must have --hl before it to enable highlighting. See the
# Debugging section for more information.
# In this instance, only simpleAI gets highlighting.
python main.py --hl ai/simpleai.py ai/basepatroller.py

# Help
python main.py --help

# Run game via appengine. The app engine server is specified in # app.yaml.
# By default, it will hit dmangame-app.appspot.com, which
# will have the version of the code in github + the latest dmanai/ available.
# Note: You should need to set APPENGINE_LOCAL to False for this to work

# The results should get posted to
# http://dmangame-app.appspot.com
python main.py dmanai/okay/rushai.py dmanai/bob/expand-then-search.py -m maps/macro.py --app-engine

# Using remote AI
# The format of a remote AI is:
# github_user:path_to_ai_module
# The AI is then downloaded from that github user's fork of dmanai and used
# as a player
#
# The following loads goose.py (with okay.py as a required dependency)
# and expand then search from github.com/okayzed/dmanai
python main.py okayzed:okay/goose.py okayzed:bob/expand-then-search.py

See Also:

I've been a fan of AI based games for a while, such as the [Google AI Challenge][g_src] and the [Queue ICPC Challenge][i_src]. They are fun and challenging (could you tell from their titles?) [g_src]: http://ai-contest.com [i_src]: http://queue.acm.org/icpc/