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Planning with Markov Decision Processes: An AI Perspective (Synthesis Lectures on Artificial Intelligence and Machine Learning)

Mausam, Andrey Kolobov




[PDF.fx33] Planning with Markov Decision Processes: An AI Perspective (Synthesis Lectures on Artificial Intelligence and Machine Learning)

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 | #2023276 in Books |  2012-07-03 | Original language:English | PDF # 1 |  9.25 x.48 x7.50l,.82 | File type: PDF | 210 pages

||0 of 0 people found the following review helpful.| Good|By Flavio Truzzi|This book is definitely an excellent start for those who want to start studying Markov decision processes and reinforcement learning, it covers from the very basic to some new advances in the planning teory.

Beware that the writing is very direct and it does not soften the way if you are not familiar with math.

Markov Decision Processes (MDPs) are widely popular in Artificial Intelligence for modeling sequential decision-making scenarios with probabilistic dynamics. They are the framework of choice when designing an intelligent agent that needs to act for long periods of time in an environment where its actions could have uncertain outcomes. MDPs are actively researched in two related subareas of AI, probabilistic planning and reinforcement learning. Probabilistic planning assu...

You easily download any file type for your device.Planning with Markov Decision Processes: An AI Perspective (Synthesis Lectures on Artificial Intelligence and Machine Learning)   |  Mausam, Andrey Kolobov. A good, fresh read, highly recommended.

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