A Deep Dive into Monte Carlo Tree Search

A Deep Dive into Monte Carlo Tree Search

  • May 21, 2018
Table of Contents

A Deep Dive into Monte Carlo Tree Search

The very first Go AIs used multiple modules to handle each aspect of playing Go – life and death, capturing races, opening theory, endgame theory, and so on. The idea was that by having experts program each module using heuristics, the AI would become an expert in all areas of the game. All that came to a grinding halt with the introduction of Monte Carlo Tree Search (MCTS) around 2008.

MCTS is a tree search algorithm that dumped the idea of modules in favor of a generic tree search algorithm that operated in all stages of the game. MCTS AIs still used hand-crafted heuristics to make the tree search more efficient and accurate, but they far outperformed non-MCTS AIs. Go AIs then continued to improve through a mix of algorithmic improvements and better heuristics.

In 2016, AlphaGo leapfrogged the best MCTS AIs by replacing some heuristics with deep learning models, and AlphaGoZero in 2018 completely replaced all heuristics with learned models.

Source: moderndescartes.com

Tags :
Share :
comments powered by Disqus

Related Posts

Transfer Learning

Transfer Learning

Transfer Learning is the reuse of a pre-trained model on a new problem. It is currently very popular in the field of Deep Learning because it enables you to train Deep Neural Networks with comparatively little data. This is very useful since most real-world problems typically do not have millions of labeled data points to train such complex models.

Read More
Crossbar Pushes Resistive RAM into Embedded AI

Crossbar Pushes Resistive RAM into Embedded AI

Resistive RAM technology developer Crossbar says it has inked a deal with aerospace chip maker Microsemi allowing the latter to embed Crossbar’s nonvolatile memory on future chips. The move follows selection of Crossbar’s technology by a leading foundry for advanced manufacturing nodes. Crossbar is counting on resistive RAM (ReRAM) to enable artificial intelligence systems whose neural networks are housed within the device rather than in the cloud.

Read More
The Nengo Neural Simulator

The Nengo Neural Simulator

Nengo is a graphical and scripting based Python package for simulating large-scale neural networks. Nengo can create sophisticated spiking or non-spiking neural simulations with sensible defaults in a few lines of code. Yet, Nengo is highly extensible and flexible.

Read More