X-Git-Url: https://git.ucc.asn.au/?p=progcomp10.git;a=blobdiff_plain;f=rps%2Ftrunk%2FREADME;fp=rps%2Ftrunk%2FREADME;h=0000000000000000000000000000000000000000;hp=8587cf5d242fbdf26f12a161a5ad24c061b727c7;hb=e9a8105a8f22404f4ac550d79954eaa6b7f5d8ff;hpb=4597b27a44522a5c2785cc23029435f44f60ea55

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-Hi there,
-
-Thanks for taking interest in the UCC Programming Competition 2008. If you 
-don't already know what it's all about, check out the information provided in 
-the docs directory, which contains a full and authoritative* description for
-the running of the competition.
-
-This file is by no means complete, and not ready for circulation.
-
-The first thing you'll probably want to do is see it work. Try running:
-
-./simulate -v
-
-to see the sample agents duke it out for up to 150 rounds (the current sample
-agents suck - rounds either go for seconds or for ages). After that, take a
-look at sampleAgents.py to see how agents are implemented on top of the
-BaseAgent and LearningAgent classes. When you're ready to try out your own,
-edit the first few lines of simulate.py to include your agent.
-
-...and if all you're interested in is participating, that's it! You can stop
-reading, and start work on the agent that will outsmart them all!
-
-Contributor instructions:
-
-BaseAgent, LearningAgent and Supervisor are all implemented in uccProgComp.py.
-The 'select' algorithm, responsible for choosing agents for battle and
-determining when a round is finished, is the hottest part of the code and the
-most open to discussion and change. 
-
-Unfortunately, it is not an easy bit of code to understand. Once upon a time,
-in builds long past, it used friendly O(n) operations and conveniently wasted
-memory on simple tasks. After hours of profiling, it is a little more complex,
-but with a bit of background to how the supervisor operates you shouldn't have
-much trouble working out the rest:
-
-1.) A copy of the current population list is made at the beginning of the round
-representing the agents who can still fight. This reduces finding valid agents
-from O(n) to O(1). I call it the 'remaining' list.
-2.) Agents must remember their index in the population list. This is because it
-would be O(n) to determine their index in the population list (to remove them
-when they die) from their index in the 'remaining' list. Agents have this value
-stored at the beginning of the round - O(n) at the beginning of the round is
-far preferable to O(n) for every death.
-3.) The actual removal of agents from the population list must happen all at
-once in reverse numeric index order at the end of the round so that the stored
-index that agents have does not become stale. 
-
-There are problems. It's not perfect, but it's relatively fast and powerful and
-quite easy to adjust or reimplement once you get your head around it. I'm very
-much open to suggestion for improvement (especially in the form of patches) and
-welcome all help, constructive criticism, derisive criticism and death threats.
-
-Things to be done:
-
-1.) Pretty graphs! Iterate () returns a collection of statistics about each of
-the classes, which can be seen used in simulate.py. There are plenty of
-plotting packages out there that can turn this information into impressive
-charts.
-2.) More built-in functionality for BaseAgent and LearningAgent. They could
-both do with a few more utility functions for competitors to use.
-3.) A more succint set of rules and documentation.
-
-Thanks for reading!
-Luke
-
-* Or rather, it wil by the time this package is ready for distribution.