AlphaZero is a revolutionary reinforcement learning agent that can play complex board games like Go, chess, and shogi. It is a computer program created by DeepMind, a subsidiary of Alphabet Inc. AlphaZero uses deep neural networks and Monte Carlo tree search to learn how to play a game without human input.
History of AlphaZero
AlphaZero was first introduced in 2017, when it defeated the world's strongest chess engine, Stockfish. The program was trained for four hours of self-play and then eva
If you are interested in artificial intelligence and reinforcement learning, then you have probably heard of MuZero. It is one of the latest models for learning decision-making procedures in a range of contexts, including simple games, difficult board games like Go, and even arcade games. MuZero was introduced in December 2019, as a successor to DeepMind's earlier model-based success, AlphaZero. MuZero builds upon AlphaZero's search and search-based policy iteration algorithms, but with the adde
Introduction to TD-Gammon
TD-Gammon is a program that uses a combination of artificial intelligence and machine learning to play Backgammon. Created in the early 1990s, TD-Gammon was the first program to showcase a neural network that could learn to play a game through self-play without human intervention.
TD-Gammon was born out of a collaboration between the computer scientists Gerald Tesauro and Jonathan Schaeffer. The goal was to use machine learning techniques to create a program that coul