# Convolutional Monte Carlo Rollouts in Go

arXiv: https://arxiv.org/abs/1512.03375 · HTML: https://mlsanity.com/paper/1512.03375/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Dec 2015.

## Built on by (most cited first, 1 of 1)

- [A Bayesian Approach to Online Planning](https://mlsanity.com/paper/2406.02103/) (2024)

## Abstract (arXiv)

In this work, we present a MCTS-based Go-playing program which uses convolutional networks in all parts. Our method performs MCTS in batches, explores the Monte Carlo search tree using Thompson sampling and a convolutional network, and evaluates convnet-based rollouts on the GPU. We achieve strong win rates against open source Go programs and attain competitive results against state of the art convolutional net-based Go-playing programs.