Monte-Carlo Planning: Basic Principles and Recent Progress
published: Nov. 15, 2010, recorded: October 2010, views: 12289
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Many planning applications are difficult to model in standard domain description languages. However, with out the limitations of a particular language, it is often possible to obtain or construct an exact or approximate simulator of the application domain. Monte-Carlo planning is an area that studies algorithms for sequential decision making when such a simulator is available. In recent years, advances in Monte-Carlo planning have lead to significant advances in applications ranging from computer networking, to real-time strategy games, to computer Go. This tutorial will cover the basic principles and theory underlying Monte-Carlo planning and also the recent advances. Emphasis will be placed on practical approaches with illustrating applications. The tutorial will start from first principles and will not assume prior knowledge of Monte-Carlo techniques.
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !