CombatWiz 0.12

CombatWiz is a combat simulation intended to determine the victory probabilities
of combatants using Monte Carlo simulation methods.

Current Status: Allows combat between two sides, and produces simple output.

#Next Steps:

* Creature editor
* Graphical output
* Map-awareness in which only one object can occupy a block
* Missile weapons
* Intelligent manuevering
* Surrender, Panic, Fleeing
* Changing weapons
* Multiple attacks per round
* Special effect attacks

#Its objectives include:

* run on linux or mac
* web front-end
* run multiple scenarios (each many times) to determine best tactics

#Example Run:

$ combatwiz_runner.py --charid1 3 --charid2 2 --charid3 4 --iterations 1000 --charfile data/characters.csv

char1
----------------------------------------------------------------
charid: char1 side: side-2
critid: 2 name: orc_chieftain
hd: 2 hp: 13
ac: 7 race: orc
class1: monster class1_level: 0
attack1_thaco: 18 attack1_damage: 2-9
vision: Infra-6 move: 12

char3
----------------------------------------------------------------
charid: char3 side: side-2
critid: 4 name: giant
hd: 0 hp: 50
ac: 4 race: giant
class1: monster class1_level: 10
attack1_thaco: 6 attack1_damage: 11-20
vision: standard move: 12

char2
----------------------------------------------------------------
charid: char2 side: side-1
critid: 3 name: paladin
hd: 0 hp: 86
ac: -3 race: human
class1: paladin class1_level: 8
attack1_thaco: 10 attack1_damage: 10-17
vision: standard move: 8
----------------------------------------------------------------

For: paladin
Games: 1000
Total Wins: 740
Total Damage Taken: 31247
Total Rounds Required: 4995
Mean Rounds Required: 6.8
Percentage of Wins: 74
Mean PCT HP Taken: 49%

For: orc_chieftain
Games: 1000
Total Wins: 7
Total Damage Taken: 10
Total Rounds Required: 45
Mean Rounds Required: 6.4
Percentage of Wins: 0
Mean PCT HP Taken: 11%

For: giant
Games: 1000
Total Wins: 260
Total Damage Taken: 6884
Total Rounds Required: 2069
Mean Rounds Required: 8.0
Percentage of Wins: 26
Mean PCT HP Taken: 52%


#Installation

* Using [pip](http://www.pip-installer.org/en/latest/) (preferred) or [easyinstall](http://peak.telecommunity.com/DevCenter/EasyInstall):

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TBD
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* Or install manually from [pypi]:

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TBD
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#Dependencies

* Python 2.6 or Python 2.7



#Licensing

* Gristle uses the BSD license - see the separate LICENSE file for further
information


#Copyright

* Copyright 2013 Ben Farmer, Ken Farmer