Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 3

Evaluation value

The relationship between the evaluation value and the winning percentage is expressed by the following formula. It is an ordinary sigmoid function. r: Win rate x: Evaluation value a: Constant. The larger a is, the steeper the change in the winning percentage per evaluation value. It seems that a = 1/600 is often used in Shogi AI. In the USI protocol, it seems that the value of one step is expressed as an evaluation value of 100 points. When a = 1/600, it seems that one step will be 100 points.

Recommended Posts

Deep Learning with Shogi AI on Mac and Google Colab Chapter 11

Deep Learning with Shogi AI on Mac and Google Colab Chapter 8

Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 3

Deep Learning with Shogi AI on Mac and Google Colab Chapter 7

Deep Learning with Shogi AI on Mac and Google Colab Chapter 10

Deep Learning with Shogi AI on Mac and Google Colab Chapter 7 5-7

Deep Learning with Shogi AI on Mac and Google Colab Chapter 9

Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 3

Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 3

Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 1-2

Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 3

Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 3 ~ 5

Deep Learning with Shogi AI on Mac and Google Colab Chapter 7 9

Deep Learning with Shogi AI on Mac and Google Colab Chapter 8 5-9

Deep Learning with Shogi AI on Mac and Google Colab Chapter 8 1-4

Deep Learning with Shogi AI on Mac and Google Colab Chapter 12 3

Deep Learning with Shogi AI on Mac and Google Colab Chapter 7 8

Deep Learning with Shogi AI on Mac and Google Colab Chapter 7 1-4

Deep Learning with Shogi AI on Mac and Google Colab

Deep Learning with Shogi AI on Mac and Google Colab Chapters 1-6

Learn with Shogi AI Deep Learning on Mac and Google Colab Use Google Colab

Deep Learning on Mac and Google Colab Words Learned with Shogi AI

Machine learning with Pytorch on Google Colab

About learning with google colab

Steps to quickly create a deep learning environment on Mac with TensorFlow and OpenCV

Play with Turtle on Google Colab

Use MeCab and neologd with Google Colab

"Learning word2vec" and "Visualization with Tensorboard" on Colaboratory

Deep Learning from scratch The theory and implementation of deep learning learned with Python Chapter 3

Install selenium on Mac and try it with python

Deep learning image analysis starting with Kaggle and Keras

[AI] Deep Metric Learning

Extract music features with Deep Learning and predict tags

"Deep Learning from scratch" Self-study memo (No. 14) Run the program in Chapter 4 on Google Colaboratory

[Google Colab] How to interrupt learning and then resume it

Recognize your boss and hide the screen with Deep Learning

An error that stumbled upon learning YOLO on Google Colab

Machine learning environment settings based on Python 3 on Mac (coexistence with Python 2)

HIKAKIN and Max Murai with live game video and deep learning

Easy deep learning web app with NNC and Python + Flask

Try deep learning with TensorFlow

Deep Kernel Learning with Pyro

Plotly Dash on Google Colab

Try Deep Learning with FPGA

Catalina on Mac and pyenv

Generate Pokemon with Deep Learning

Create AtCoder Contest appointments on Google Calendar with Python and GAS

Build a Python environment on your Mac with Anaconda and PyCharm

Error and solution when installing python3 with homebrew on mac (catalina 10.15)

How to run Jupyter and Spark on Mac with minimal settings

The strongest way to use MeCab and CaboCha with Google Colab

[Reading Notes] Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow Chapter 1

Install lp_solve on Mac OS X and call it with python.

Try Deep Learning with FPGA-Select Cucumbers

Cat breed identification with deep learning

Deep Learning / Deep Learning from Zero Chapter 3 Memo

tensor flow with anaconda on mac

MQTT on Raspberry Pi and Mac

Make ASCII art with deep learning

Deep Learning / Deep Learning from Zero 2 Chapter 5 Memo

Try deep learning with TensorFlow Part 2