-
Current version of OpenAI Gym doesn't support creating Go environments with custom adversary policies. The code that illustrates this:
```python
from gym.envs.board_game import go
import random
…
-
I made a simple plain vanilla NN in Python with adjustable layers. This is its take on the MNIST data set with 30 hidden nodes:
Epoch 0: 9062 / 10000
Epoch 1: 9196 / 10000
…
-
Termin: 14.12.2016 19:00
- [x] Location
- [x] [Event anlegen](http://hamburg.onruby.de/admin/)
- [x] [Talks / Format](https://github.com/rughh/planning/wiki/Speaker-Checklist)
- [x] Promo auf Twit…
-
v3.co.uk
AakList
-
http://mp.weixin.qq.com/s/-wSYLu-XvOrsST8_KEUa-Q
朱松纯 加州大学洛杉矶分校UCLA
统计学和计算机科学教授
视觉、认知、学习与自主机器人中心主任
VCLA@UCLA
2017年11月02日 刊登于 《视觉求索》微信公众号
- [x] [Talks / Format](https://github.com/rughh/planning/wiki/Speaker-Checklist)
- [x] Promo auf Twitt…
-
Currently, TPOT allows users to specify the number of GP generations to run optimization for. This makes sense for users who are experienced with GP, but not so much for the general user.
We should a…
-
GnuGo 3.8 and BetaGo both report "connection error",
and I tested both Engines without Sabaki and they are in working order.
-
I want to make the rollout provide a better estimate. This way we don't have to expand the tree so deep. One way to do this is to use a convnet to provide a policy as per. alphago.
Using this in the…
-
Thank you for sharing first. So in other words, it use only DNN to predict the next move other than AlphaGo, which used also the Monte Carlo Tree Search combined with DNNs.