Difference between revisions of "User:Flixx/GSoC 2013/AI: AI: Refactor recruitment algorithm"
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A AI opponent have to decide in a separate phase which units to recruit. Right now the default recruitment algorithm is very simple and can be improved in many ways. I want to make the AI recruiting better, more fun to play against and more configurable by a scenario editor. | A AI opponent have to decide in a separate phase which units to recruit. Right now the default recruitment algorithm is very simple and can be improved in many ways. I want to make the AI recruiting better, more fun to play against and more configurable by a scenario editor. | ||
Revision as of 11:43, 23 April 2013
| This page is related to Summer of Code 2013 |
| See the list of Summer of Code 2013 Ideas |
| This is a Summer of Code 2013 student page |
Contents
Description
flix: Refactor recruitment algorithm
A AI opponent have to decide in a separate phase which units to recruit. Right now the default recruitment algorithm is very simple and can be improved in many ways. I want to make the AI recruiting better, more fun to play against and more configurable by a scenario editor.
Make it better
(In terms of harder to play against)
Map Analysis
Previous attempts have been made to this:
- analyze_potential_recruit_movements() analyzes nearby targets and how to reach them.
- the "Formula AI dev"-Recruitment uses the terrain near to villages ("important locations") and recruits units which defend good in those areas. According to Crab_ the algorithm easily beats the RCA AI (default-AI). The algorithm is written in Formula-AI and hard to understand (and probably therefore not in use). Additionally Formula-AI is not longer supported in future developments.
In my project I want to refactor the "Formula AI dev"-Recruitment in C++, test it, improve it and make it easy to configure.
Combat Analysis
The current RCA AI make much use of a combat analysis. This works actually pretty well. The problem is, that the RCA AI uses not much more than this analysis. Therefor it happens, that the AI will overestimate strong units according to the current game situation. It is often better to have more weaker units. Furthermore it can happen, that only one type of unit is recruited. But I think the Combat Analysis as such doesn't need a big refactoring. The goal should be to weight Combat Analysis against other methods like Map Analysis.
Therefore I want to spend only little time in testing and improving the current Combat Analysis. (But of curse I want to determine a appropriate weight and find the right place for Combat Analysis in the overall solution)
Counter Recruitment Strategies
In order to recruit the best units for a set of enemy units and make the best use of a combat analysis, it is sometimes useful to wait for the enemy to recruit. (Not spend all money in the first round). The RCA AI will always recruit when it has enough gold available. This can be improved. The hardest part when implementing this is to decide when such a strategy is appropriate.
I want first to introduce a state "Counter Recruitment". When the AI is in this state it will first wait (and discover) enemy units before spending all the money. Then I will test (via benchmarking) in which cases it is useful for the AI to enter or leave this state.
Make it more Fun
In terms of recruitment more fun is achieved when the AI is recruiting not only one type but a good mix of all available units. This can easily be achieved by just favor rare units. The hard part here is again, how to weight it against other options.
Make it more configurable
Above I talked a bit about weighting things. Of course I should find the best default-weights for the multiplayer modus. But this weights could easily be changed by aspects. One could introduce aspects like "combat-weight, terrain-weight, counter-recruitment, diversity" and let a scenario editor pick the wished combination.
Purposes Idea
For the Idea see this page: User:Flixx/GSoC 2013/Idea AI Recruitment: Purposes
In the scope of this project I want to take some time to implement a Proof of Concept of this idea for further evaluation. I think it is a good idea but I don't want to define the implementation of this as a project goal. Probably Purpose-Driven-Recruitment will get too complex, and I don't want to fail the goals. Though I want to plan some time at the end of the summer for this idea to see if it's worth something.
Multiple Leader
TODO
Set of Goals / Milestones
- Refactor the "Formula AI dev"-Recruitment in C++, test it, improve it and make it easy to configure.
- Implement a Counter-Recruitment-Strategy and find good conditions when to use it
- Implementing a system to favor rare units
- Find good default-weights for all sub-algorithms
- Make those weights configurable
- TODO: Multiple Leader
- Implementing a Proof of Concept for the Purpose Idea and test it
IRC
flix
Questionnaire
I put the Questionnaire on a separate page. I can join it later.