Explain the role of Monte Carlo Tree Search (MCTS) in AlphaGo and how it integrates with policy and value networks.
Tuesday, 11 June 2024
by EITCA Academy
Monte Carlo Tree Search (MCTS) is a pivotal component of AlphaGo, an advanced artificial intelligence system developed by DeepMind to play the game of Go. The integration of MCTS with policy and value networks forms the core of AlphaGo's decision-making process, enabling it to evaluate and select optimal moves in the complex search space of
- Published in Artificial Intelligence, EITC/AI/ARL Advanced Reinforcement Learning, Case studies, Classic games case study, Examination review
Tagged under:
AlphaGo, Artificial Intelligence, Deep Learning, MCTS, Policy Networks, Value Networks
What is the significance of Monte Carlo Tree Search (MCTS) in reinforcement learning, and how does it balance between exploration and exploitation during the decision-making process?
Tuesday, 11 June 2024
by EITCA Academy
Monte Carlo Tree Search (MCTS) is a pivotal algorithm in the domain of reinforcement learning, particularly in the context of planning and decision-making under uncertainty. Its significance stems from its ability to efficiently explore large and complex decision spaces, making it particularly useful in applications such as game playing, robotic control, and other areas where
- Published in Artificial Intelligence, EITC/AI/ARL Advanced Reinforcement Learning, Deep reinforcement learning, Planning and models, Examination review
Tagged under:
Artificial Intelligence, Game Playing, MCTS, Reinforcement Learning, Robotic Control, UCT