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21
Jul
A Summary of AlphaZero – Training an agent to play classical games Tabula Rasa

Author : Shubha Manikarnike Submitted on : 5 Sep 2020 Abstract – This paper explains the AlphaGoZero algorithm which was developed by Google Deepmind. It achieved super human performance in the Game of GO. It discusses Monte Carlo Tree Search (MCTS) algorithm which is integrated with an Actor Critic approach. The agent learns how to […]

Posted in: Gaming, papers, Reinforcement Learning,
20
Aug
AlphaZero with Monte Carlo Tree Search

#CellStratAILab #disrupt4.0 #WeCreateAISuperstars #WhereLearningNeverStops In recent weeks, I had presented a session on “AlphaZero with Monte Carlo Tree Search” algorithm at the CellStrat AI Lab. This is an algorithm developed by Google Deepmind in 2016. It mastered the game of GO and beat the 18-time world champion at the time Lee Sedol. Go is an ancient Chinese abstract strategy […]

Posted in: Gaming, Reinforcement Learning, Robotics,
Tags: Actor Critic, AlphaGO, AlphaZero, deepmind, Game Tree, MCTS, Monte Carlo Tree Search, policy evaluation, policy improvement, policy iteration, reinforcement learning, UCT, Upper Confidence Bound,