Efficiency of three forward-pruning techniques in shogi: Futility pruning, null-move pruning, and Late Move Reduction (LMR)

By Kunihito Hoki, M. Muramatsu. 2012

18 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Economics and Econometrics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Matthew Lai
2. Tomoyuki Kaneko
3. Kunihito Hoki
4. Peter W. Battaglia

In Computer Vision and Pattern Recognition

1. Matthew Lai
2. Tomoyuki Kaneko
3. Kunihito Hoki
4. Peter W. Battaglia

In Economics and Econometrics

1. Matthew Lai
2. Tomoyuki Kaneko
3. Kunihito Hoki

Citations in the corpus

• Giraffe: Using Deep Reinforcement Learning to Play Chess (2015, methodology): “This technique is known as late move reduction [25].”
• Large-Scale Optimization for Evaluation Functions with Minimax Search (2014, methodology): “Most of the experiments described in this section used Bonanza, whose source code is available online (Hoki & Muramatsu, 2012).”