Simulated Annealing Monte Carlo Tree Search for Large POMDPs
Kai Xiong, Hong Jiang · 2014
Many planning and control problems can be modeled as large POMDPs, but very few can be solved scalably because of their computational complexity. This paper proposes a Simulated Annealing based on the Monte Carlo Tree Search for large POMDPs. The proposed algorithm determines an acceptance probability of sampling a back-propagation's outcome in the simulated annealing process. The experiments show that the proposed SAMCTS (Simulated Annealing Monte Carlo Tree Search) outperforms the original Simulated Annealing algorithm when applied to a large POMDP benchmark problem.