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We know that AI is one of the most important part of Game Programming. Bayesian networks is one of the core part of AI at Game Programming.

Bayesian networks are graphs that compactly represent the relationship between random variables for a given problem. These graphs aid in performing reasoning or decision making in the face of uncertainty.

I am utilizing the monte carlo method and genetic algorithms.

  • But this take too much time and sometimes crashes due to memory.

Is there any way to implement this efficiently?

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Care to give an example as to what goal you wish to achieve using this system, where will this AI be implemented? Just curious – zehelvion Sep 25 '12 at 14:06
up vote 4 down vote accepted

Try to implement your network in an existing Bayesian tool like these:

This will help you see if the issue is the complexity of your network or your code.

I suggest you Google for "bayesian network" and "real time". There are many articles that talk about how to speed up processing.

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better reference :) – Md. Mahbubur R. Aaman Sep 25 '12 at 9:47

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