Policy or Value ? Loss Function and Playing Strength in AlphaZero
Por um escritor misterioso
Last updated 28 maio 2024
Results indicate that, at least for relatively simple games such as 6x6 Othello and Connect Four, optimizing the sum, as AlphaZero does, performs consistently worse than other objectives, in particular by optimizing only the value loss. Recently, AlphaZero has achieved outstanding performance in playing Go, Chess, and Shogi. Players in AlphaZero consist of a combination of Monte Carlo Tree Search and a Deep Q-network, that is trained using self-play. The unified Deep Q-network has a policy-head and a value-head. In AlphaZero, during training, the optimization minimizes the sum of the policy loss and the value loss. However, it is not clear if and under which circumstances other formulations of the objective function are better. Therefore, in this paper, we perform experiments with combinations of these two optimization targets. Self-play is a computationally intensive method. By using small games, we are able to perform multiple test cases. We use a light-weight open source reimplementation of AlphaZero on two different games. We investigate optimizing the two targets independently, and also try different combinations (sum and product). Our results indicate that, at least for relatively simple games such as 6x6 Othello and Connect Four, optimizing the sum, as AlphaZero does, performs consistently worse than other objectives, in particular by optimizing only the value loss. Moreover, we find that care must be taken in computing the playing strength. Tournament Elo ratings differ from training Elo ratings—training Elo ratings, though cheap to compute and frequently reported, can be misleading and may lead to bias. It is currently not clear how these results transfer to more complex games and if there is a phase transition between our setting and the AlphaZero application to Go where the sum is seemingly the better choice.
AlphaZero, a novel Reinforcement Learning Algorithm, in JavaScript, by Carlos Aguayo
Policy or Value ? Loss Function and Playing Strength in AlphaZero-like Self- play
Strength and accuracy of policy and value networks. a Plot showing the
PDF) Alternative Loss Functions in AlphaZero-like Self-play
Electronics, Free Full-Text
AlphaGo Zero – How and Why it Works – Tim Wheeler
🔵 AlphaZero Plays Connect 4
AlphaZero, Vladimir Kramnik and reinventing chess
Lecture 13: Reinforcement learning
Policy or Value ? Loss Function and Playing Strength in AlphaZero-like Self- play
Recomendado para você
-
AlphaZero really is that good28 maio 2024
-
Mastering the game of Go without human knowledge28 maio 2024
-
Has the Alpha Zero chess program been made to play the Evans Gambit against itself, in an attempt to discover whether that gambit, with best play, is theoretically sound or whether White28 maio 2024
-
AlphaZero paper published in journal Science : r/baduk28 maio 2024
-
AlphaZero - Chessprogramming wiki28 maio 2024
-
How DeepMind's AlphaGo Became the World's Top Go Player, by Andre Ye28 maio 2024
-
Alpha S 2 Pickleball Paddle Bundle - Pickleball Paddle Shop28 maio 2024
-
Contributing to Leela Chess Zero. Creating the Caissa of Chess engines. - Leela Chess Zero28 maio 2024
-
PDF] Reproducibility via Crowdsourced Reverse Engineering: A Neural Network Case Study With DeepMind's Alpha Zero28 maio 2024
-
PDF] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm28 maio 2024
você pode gostar
-
4 Cores: jogo divertido28 maio 2024
-
animes de rei demonios 202328 maio 2024
-
O que significa fight off your demons? - Pergunta sobre a Inglês (EUA)28 maio 2024
-
Bethesda's Stunning Redfall Xbox Series X Console Is Up For Grabs28 maio 2024
-
Jogo de moto com grau e corte - Baixar APK para Android28 maio 2024
-
Hillsong Church's Celebrity History and Scandals, Explained28 maio 2024
-
Sum 41 Comic Shirt Sweatshirt 90S Vintage Book Art Pieces28 maio 2024
-
Cartoon Video & Gif Maker 4.2 Free Download28 maio 2024
-
En En no Shouboutai / Fire Force, novo PV apresenta o personagem Akitaru Obi – Tomodachi Nerd's28 maio 2024
-
DRAGON BALL Z – FIGURINE SON GOKU & GOHAN & BIPED ROBOT DESKTOP REAL McCOY EX Precio de Preventa: 220 mil Efectivo/transferencia Se…28 maio 2024