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Targeting systems that utilize a detailed log of enemy data to predict where the target will be. The classic version of this is PatternMatching. Can work very well against simple bots and is currently a great way to hit WaveSurfers, but suffers from a long learning time and high processor loads, and the need for DealingWithSkippedTurns.

PatternMatching - Checking the targets current actions against things they had done in the past. The main goal is trying to balance precision with the fuzziness factor, and keeping it as fast as possible. Subsets of this are MogBot style, SymbolicPatternMatching, and whatever you want to call TronsGun.

NeuralTargeting - Using neural nets to predict enemy behavior. Rather obscure and very high level, but could have definite potential.

CommandReconstructionTargeting? - A very obscure targeting method. Analyzes enemy behavior to calculate the commands that would give the result. Then once given the command list, attempts to reconstruct the movement code and use that to predict movement. The HolyGrail of Targeting if implemented.

SOOLTargeting - The log is self ordering. Locke uses it successfully. A description of the algorithm can be found on Locke's page.

Why are neural networks counted as log targeting? You use certain patterns (e.g. your enemy's velocity, heading, position) to train your neural network, but I doubt that you can find back what your enemy's bot was doing X ticks ago, like in a log. --Dummy

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Last edited January 17, 2006 0:02 EST by Voidious (diff)