Search
Skip to Search Results
Filter
Departments
Supervisors
Author / Creator / Contributor
Subject / Keyword
- 1Heuristic Search
- 1Model Uncertainty
- 1Monte Carlo Tree Search
- 1MuZero
- 1Reinforcement Learning
- 1deep learning
Year
Collections
Languages
Item type
-
Fall 2022
Monte Carlo Tree Search (MCTS) is a popular tree search framework for choos- ing actions in decision-making problems. MCTS is traditionally applied to applications in which a perfect simulation model is available. However, when the model is imperfect, the performance of MCTS drops heavily. In...
-
Spring 2023
The intent of this thesis is to develop a high-performance open-source system that plans with a learned model and to understand the algorithm through extensive analysis. We formulate the problem of maximizing accumulated rewards in Markov Decision Processes, and we frame playing games as such...
1 - 2 of 2