All of these use Markov Chains: A weather simulator, that guesses tomorrow's weather by looking at today's state and retrieving the probability of case x tomorr

All of these use Markov Chains: A weather simulator, that guesses tomorrow's weather by looking at today's state and retrieving the probability of case x tomorrow. Run it a few times, see what the weather patterns look like. A chat between two bots, that use nlp and maybe an algorithm to check if they make sense. See if they always finish with the same results. Then, apply this to the human mind and reflect. Great resources: http://blog.electric-cloud.com/2009/09/15/using-markov-chains-to-generate-test-input/ http://blog.electric-cloud.com/2009/09/15/using-markov-chain... (might want to implement the bots from this) http://en.wikipedia.org/wiki/Examples_of_Markov_chains http://en.wikipedia.org/wiki/Examples_of_Markov_chains (where the weather idea came from) http://uswaretech.com/blog/2009/06/pseudo-random-text-markov-chains-python/ http://uswaretech.com/blog/2009/06/pseudo-random-text-markov... (simple markov chains in python) bonus: make the bots have a chat room P.S. This might not easily tie in with GarlicSim, but I thought these are very interesting topics.