Has anyone thought about or attempted to model game AI with Markov Chains instead of decision trees? Ex: NPCs, wildlife or enemies that use Markov Chains to react to their surroundings.
Not sure about individual-scale models, but Markov Chains are common in Mathematical Ecology. You can do quite a lot in animal group modeling with transition matrices and basic probability theory. This is a good book if you can get it cheap (like most monograph textbooks):
http://www.amazon.com/Introduction-Stochastic-Processes-Biol...
Also, props to submission author Victor Powell. Those force-directed graphs are visually interesting, add to the article, and are even responsive (try changing the window size).
Comments
Has anyone thought about or attempted to model game AI with Markov Chains instead of decision trees? Ex: NPCs, wildlife or enemies that use Markov Chains to react to their surroundings.
Not sure about individual-scale models, but Markov Chains are common in Mathematical Ecology. You can do quite a lot in animal group modeling with transition matrices and basic probability theory. This is a good book if you can get it cheap (like most monograph textbooks): http://www.amazon.com/Introduction-Stochastic-Processes-Biol...
Also, props to submission author Victor Powell. Those force-directed graphs are visually interesting, add to the article, and are even responsive (try changing the window size).
Just a decision tree with a probability of transitioning to a branch?