Journal of Intelligent Learning Systems and Applications

Journal of Intelligent Learning Systems and Applications

ISSN Print: 2150-8402
ISSN Online: 2150-8410
www.scirp.org/journal/jilsa
E-mail: jilsa@scirp.org
"Self-Play and Using an Expert to Learn to Play Backgammon with Temporal Difference Learning"
written by Marco A. Wiering,
published by Journal of Intelligent Learning Systems and Applications, Vol.2 No.2, 2010
has been cited by the following article(s):
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[1] Self-play reinforcement learning with comprehensive critic in computer games
2021
[2] Analysis of Hyper-Parameters for Small Games: Iterations or Epochs in Self-Play?
2020
[3] Warm-Start AlphaZero Self-Play Search Enhancements
2020
[4] Reinforcement Learning agents playing Hearthstone: The influence of state description when learning in a large, partially observable state space
2020
[5] Learning to Play: Reinforcement Learning and Games
2020
[6] Applying Reinforcement Learning with Monte Carlo Tree Search to The Game of Draughts
2019
[7] Alternative loss functions in alphazero-like self-play
2019
[8] Policy or Value? Loss Function and Playing Strength in AlphaZero-like Self-play
2019
[9] Hyper-Parameter Sweep on AlphaZero General
2019
[10] Competitive Evolution Multi-Agent Deep Reinforcement Learning
2019
[11] A Multi-agent Design of a Computer Player for Nine Men's Morris Board Game using Deep Reinforcement Learning
2019
[12] Development of a Computer Player for Seejeh (AKA Seega, Siga, Kharbga) Board Game with Deep Reinforcement Learning
2019
[13] Investigating Deep Learning and Self Play in Artificial Intelligent Games
International Journal of Innovative Science, Engineering & Technology, 2018
[14] A bright future for financial agent-based models
2018
[15] Hyper Dice Backgammon of Finite Size
2018
[16] Learning to play othello without human knowledge
2016
[17] Discussion
Design of Experiments for Reinforcement Learning, 2015
[18] Decision making in multiplayer environments: application in backgammon variants
2015
[19] The Mountain Car Problem
Design of Experiments for Reinforcement Learning.Springer, 2015
[20] Reinforcement Learning
Design of Experiments for Reinforcement Learning.Springer, 2015
[21] The Truck Backer-upper Problem
Design of Experiments for Reinforcement Learning.Springer, 2015
[22] Temporal Difference Learning for the Game Tic-Tac-Toe 3D: Applying Structure to Neural Networks
Computational Intelligence, 2015 IEEE Symposium Series on, 2015
[23] Self-Optimizing Evaluation Function for Chinese-Chess.
International Journal of Hybrid Information Technology, 2014
[24] Design of experiments for reinforcement learning
2014
[25] Reinforcement Learning with Neural Networks: Tricks of the Trade
Advances in Intelligent Signal Processing and Data Mining. Springer Berlin Heidelberg, 2013
[26] Reinforcement learning in the game of Othello: Learning against a fixed opponent and learning from self-play
Adaptive Dynamic Programming And Reinforcement Learning (ADPRL), 2013 IEEE Symposium on. IEEE, 2013
[27] On Constructing Static Evaluation Function using Temporal Difference Learning
2013
[28] A Novel Technique to Find Outliers in Mixed Attribute Datasets
Computer Engineering and Applications Journal, 2013
[29] Conclusions, Future Directions and Outlook
Reinforcement Learning, 2012
[30] Improving Temporal Difference Learning Performance in Backgammon Variants
Advances in Computer Games, 2012
[31] Reinforcement learning in games
Reinforcement Learning, 2012
[32] Self-teaching adaptive dynamic programming for Gomoku
Neurocomputing, 2012
[33] On the Design and Training of Bots to Play Backgammon Variants
Artificial Intelligence Applications and Innovations. Springer Berlin Heidelberg, 2012
[34] A brief tutorial on reinforcement learning: The game of Chung Toi.
ESANN, 2011
[35] Reinforcement learning and the effects of parameter settings in the game of Chung Toi
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on. IEEE, 2011
[36] Editorial: Special Section on Reinforcement Learning and Approximate Dynamic Programming
Journal of Intelligent Learning Systems and Applications, 2010
[37] Special Section on Reinforcement Learning and Approximate Dynamic Programming.
2010
[38] Learning to Play
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