Does anyone want to comment on this paper?
https://export.arxiv.org/pdf/1806.00683
Deep Pepper Paper
Moderators: hgm, Rebel, chrisw
-
Leo
- Posts: 1080
- Joined: Fri Sep 16, 2016 6:55 pm
- Location: USA/Minnesota
- Full name: Leo Anger
Deep Pepper Paper
Advanced Micro Devices fan.
-
jdart
- Posts: 4366
- Joined: Fri Mar 10, 2006 5:23 am
- Location: http://www.arasanchess.org
Re: Deep Pepper Paper
I am not sure I understand all of it but in general it looks like a plausible approach.
They mention they don't have an ELO measure based on performance against other engines. So that makes it hard to judge how effective a system it is.
I also don't know if they have managed to overcome to tactical blindness that LC0 exhibits on occasion.
--Jon
They mention they don't have an ELO measure based on performance against other engines. So that makes it hard to judge how effective a system it is.
I also don't know if they have managed to overcome to tactical blindness that LC0 exhibits on occasion.
--Jon
-
whereagles
- Posts: 565
- Joined: Thu Nov 13, 2014 12:03 pm
Re: Deep Pepper Paper
no games, no fun, no matter 
-
saikrishnagv
- Posts: 2
- Joined: Mon Sep 24, 2018 9:42 pm
- Full name: Sai Krishna
Re: Deep Pepper Paper
Hello gang,
I am one of the authors of the paper, let me know if you have any questions. Our paper is an attempt for much faster training of self-play like algorithms. Self-play algorithms were proposed by David Barber's group https://arxiv.org/abs/1705.08439 and then followed by some papers from DeepMind
-Sai
I am one of the authors of the paper, let me know if you have any questions. Our paper is an attempt for much faster training of self-play like algorithms. Self-play algorithms were proposed by David Barber's group https://arxiv.org/abs/1705.08439 and then followed by some papers from DeepMind
-Sai