Strategy Evaluation in Extensive Games with Importance Sampling

author: Michael Johanson, Department of Computing Science, University of Alberta
published: Aug. 7, 2008,   recorded: July 2008,   views: 4436
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Description

Typically agent evaluation is done through Monte Carlo estimation. However, stochastic agent decisions and stochastic outcomes can make this approach inefficient, requiring many samples for an accurate estimate. We present a new technique that can be used to simultaneously evaluate many strategies while playing a single strategy in the context of an extensive game. This technique is based on importance sampling, but utilizes two new mechanisms for significantly reducing variance in the estimates. We demonstrate its effectiveness in the domain of poker, where stochasticity makes traditional evaluation problematic.

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Reviews and comments:

Comment1 Neeva, February 7, 2022 at 3:42 p.m.:

Very cool. I have been playing poker for a long time and have changed a lot of sites. On each of them, I got a tremendous experience of the game. I mainly play online casinos with a 10 euro deposit because I think they are the best in my country. I read a cool review about these casinos https://casinotop.at/10-euro-casino/ thanks to which I made certain conclusions. Your method looks reasonable and correct. I think I should try to understand it and try it in the game. Thank you very much, maybe it will help me.

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