"Emergence of Higher Exploration in Reinforcement Learning Using a Chaotic Neural Network"

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Book	Author(s)	Year	Publisher
Neural network analysis using Simulnet	Edward J. Rzempoluck	1998	Springer
Neural Network Learning: Theoretical Foundations	Martin Anthony; Peter L. Bartlett	1999-11	Cambridge University Press
Explanation-Based Neural Network Learning: A Lifelong Learning Approach	Sebastian Thrun	1996	Springer US
Modular learning in neural networks: a modularized approach to neural network classification	Tomas Hrycej	1992	Wiley
Java Deep LearningCookbook - Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j.	Rahul Raj	2020	Packt
Neural Network Learning and Expert Systems	Stephen I. Gallant	1993	MIT Press
Neural Network Learning and Expert Systems	Stephen I. Gallant	1993	MIT Press,
Neural network learning and expert systems	Stephen I. Gallant	1993	MIT Press
Human-Robot Interaction Control Using Reinforcement Learning	Wen Yu; Adolfo Perrusquia	2022	Wiley-IEEE Press
Hands-on Reinforcement Learning with Python. Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow	Sudharsan Ravichandiran	2018	Packt
Hands-on Reinforcement Learning with Python. Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow	Sudharsan Ravichandiran	2018	Packt
Hands-On Reinforcement Learning with Python: Master Reinforcement and Deep Reinforcement Learning Using OpenAI Gym and TensorFlow	Ravichandiran, Sudharsan	2018;2019	Packt Publishing Ltd
Animal learning and cognition: a neural network approach /	Schmajuk, Nestor A.	1997.	Cambridge University Press,
Computer Vision Using Deep Learning: Neural Network Architectures with Python and Keras	Vaibhav Verdhan	1st ed.	Apress
Neural Network Data Analysis Using Simulnet™	Edward J. Rzempoluck	1998	Springer New York
Classification of underwater signals using a back-propagation neural network	Richard Campbell Bennett	1997	Naval Postgraduate School;Available from National Technical Information Service
Deep learning with PyTorch: a practical approach to building neural network models using PyTorch	Subramanian, Vishnu	2018	Packt Publishing.
Deep learning with PyTorch: a practical approach to building neural network models using PyTorch	Subramanian, Vishnu	2018	Packt Publishing
Using Learning Contracts in Higher Education	Laycock, Mike; Stephenson, John	1993	Routledge
Advances in pattern recognition systems using neural network technologies /	Guyon, Isabelle.; Wang, Patrick S-P.	[1993], ©1993.	World Scientific,
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Chapter	Author(s)	Book	Book Authors	Year	Publisher
Emergence of Higher Exploration in Reinforcement Learning Using a Chaotic Neural Network	Yuki Goto; Katsunari Shibata	Neural Information Processing: 23rd International Conference, ICONIP 2016, Kyoto, Japan, October 16–21, 2016, Proceedings, Part I	Akira Hirose; Seiichi Ozawa; Kenji Doya; Kazushi Ikeda; Minho Lee; Derong Liu	1st ed. 2016	Springer International Publishing
Influence of the Chaotic Property on Reinforcement Learning Using a Chaotic Neural Network	Yuki Goto; Katsunari Shibata	Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part I	Derong Liu; Shengli Xie; Yuanqing Li; Dongbin Zhao; El-Sayed M. El-Alfy	1st ed. 2017	Springer International Publishing
NEURAL NETWORK & REINFORCEMENT LEARNING		Machine Learning Proceedings 1990	Bruce W. Porter and Ray J. Mooney	1990	Morgan Kaufmann
Control of Associative Chaotic Neural Networks Using a Reinforcement Learning	Norihisa Sato; Masaharu Adachi; Makoto Kotani	Advances in Neural Networks - ISNN 2004: International Symposium on Neural Networks, Dalian, China, August 19-21, 2004, Proceedings, Part I	Fuliang Yin; Jun Wang; Chengan Guo	2004	Springer Berlin Heidelberg
""Neural network and reinforcement learning""		Practical Reinforcement Learning	Farrukh Akhtar	2017	Packt Publishing
06 Emergence of Intelligence Through Reinforcement Learning with a Neural Network		Advances in Reinforcement Learning	Abdelhamid Mellouk	2011-01-14	IntechOpen
Effects of Chaotic Exploration on Reinforcement Maze Learning		Knowledge-Based Intelligent Information and Engineering Systems: 8th International Conference, Kes 2004, Wellington, New Zealand, September 20-25, 2004, Proceedings, Part I	Howlett R.J. (ed.), Jain L.C. (ed.)	2004	Springer
A Novel Neural Network Based Reinforcement Learning	Jian Fan; Yang Song; MinRui Fei; Qijie Zhao	Bio-Inspired Computational Intelligence and Applications: International Conference on Life System Modeling, and Simulation, LSMS 2007, Shanghai, China, September 14-17, 2007. Proceedings	Minrui Fei; George W. Irwin; Shiwei Ma	2007	Springer Berlin Heidelberg
On Learning Parameters of Incremental Learning in Chaotic Neural Network	Toshinori Deguchi; Naohiro Ishii	Engineering Applications of Neural Networks: 17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings	Chrisina Jayne; Lazaros Iliadis	1st ed. 2016	Springer International Publishing
On Acceleration of Incremental Learning in Chaotic Neural Network	Toshinori Deguchi; Toshiki Takahashi; Naohiro Ishii	Advances in Computational Intelligence: 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10-12, 2015. Proceedings, Part II	Ignacio Rojas; Gonzalo Joya; Andreu Catala	2015	Springer International Publishing
Reinforcement Learning by Chaotic Exploration Generator in Target Capturing Task	Koichiro Morihiro; Teijiro Isokawa; Nobuyuki Matsui; Haruhiko Nishimura	Knowledge-Based Intelligent Information and Engineering Systems: 9th International Conference, KES 2005, Melbourne, Australia, September 14-16, 2005, Proceedings, Part I	Rajiv Khosla	2005	Springer Berlin Heidelberg
Efficient Exploration in Reinforcement Learning	John Langford	Encyclopedia of Machine Learning and Data Mining	Claude Sammut; Geoffrey I. Webb	2nd ed. 2017	Springer US
Efficient Exploration in Reinforcement Learning	John Langford	Encyclopedia of Machine Learning	Claude Sammut; Geoffrey I. Webb	2010	Springer US
Naive Neural Network policy for Reinforcement Learning		Mastering TensorFlow 1. x: Advanced machine learning and deep learning concepts using TensorFlow 1. x and Keras	Armando Fandango	2018	Packt Publishing - ebooks Account
Reinforcement Learning in Neural Networks		Encyclopedia of Neuroscience	Marc D. Binder; Nobutaka Hirokawa; Uwe Windhorst	2009	Springer Berlin Heidelberg
Chaotic Exploration Generator for Evolutionary Reinforcement Learning Agents in Nondeterministic Environments	Akram Beigi; Nasser Mozayani; Hamid Parvin	Adaptive and Natural Computing Algorithms: 10th International Conference, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part II	Andrej Dobnikar; Uroš Lotrič; Branko Šter	2011	Springer Berlin Heidelberg
Chaotic Exploration Generator for Evolutionary Reinforcement Learning Agents in Nondeterministic Environmen		Adaptive and Natural Computing Algorithms: 10th International Conference, ICANNGA 2011, Ljubljana, Slovenia, April 14-16, 2011, Proceedings, Part II	Dominik Olszewski (auth.), Andrej Dobnikar, Uroš Lotrič, Branko à ter (eds.)	2011	Springer Berlin Heidelberg
Reinforcement Learning and Attractor Neural Network Models of Associative Learning	Oussama H. Hamid; Jochen Braun	Computational Intelligence: 9th International Joint Conference, IJCCI 2017 Funchal-Madeira, Portugal, November 1-3, 2017 Revised Selected Papers	Christophe Sabourin; Juan Julian Merelo; Kurosh Madani; Kevin Warwick	1st ed. 2019	Springer International Publishing
Dueling DDQN: A reinforcement-learning-aware neural network architecture		Grokking Deep Reinforcement Learning	Miguel Morales	2020	Manning Publications
A Hybrid Neural Network Model Based Reinforcement Learning Agent	Pengyi Gao; Chuanbo Chen; Kui Zhang; Yingsong Hu; Dan Li	Advances in Neural Networks -- ISNN 2010: 7th International Symposium on Neural Networks, ISNN 2010, Shanghai, China, June 6-9, 2010, Proceedings, Part I	James Kwok; Bao-Liang Lu; Liqing Zhang; Bao-Liang Lu	2010	Springer Berlin Heidelberg
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