The student will familiarize with existing Monte Carlo techniques such as Monte Carlo Tree Search and its derivatives and also with the classical formulation of planning problems. Based on this study, the student will propose how to exploit the Monte Carlo techniques to solve planning problems. This could be done by (semi-)automated reformulation of the planning problem or by proposing a set of modeling principles that would allow to manually formulate a planning problem to a form appropriate for the solving algorithm. A complementary approach is modifying the solving approach for the planning problems.
Seznam odborné literatury
Cameron Browne, Edward Powley, Daniel Whitehouse, Simon Lucas, Peter I. Cowling, Philipp Rohlfshagen, Stephen Tavener, Diego Perez, Spyridon Samothrakis and Simon Colton: A Survey of Monte Carlo Tree Search Methods, IEEE Transaction on Computational Intelligence and AI in Games, Vol. 4, No. 1, March 2012
Malik Ghallab, Dana Nau, Paolo Traverso: Automated Planning: Theory and Practice, Morgan Kaufmann, 2004