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by
Vrancx, Peter.
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Alıntı:
Decentralised reinforcement learning in Markov games / Vrancx, Peter.
by
Schwartz, Howard M., author.
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Multi-agent machine learning : a reinforcement approach / Schwartz, Howard M., author.
by
Buini, Hamid, author.
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Control System Design Automation Using Reinforcement Learning / Buini, Hamid, author.
by
Grossberg, Stephen, 1939-
ScienceDirect http://www.sciencedirect.com/science/book/9780444701176
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The adaptive brain. I : cognition, learning, reinforcement, and rhythm / Grossberg, Stephen, 1939-
by
Dutta, Sayon, author.
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Reinforcement learning with TensorFlow : a beginner's guide to designing self-learning systems with
by
Lapan, Maxim, author.
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Deep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value
by
Karim, Rezaul, author.
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, unsupervised, and reinforcement learning with tensorflow / Karim, Rezaul, author.
by
Massaron, Luca, author.
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, chatbots, and reinforcement learning / Massaron, Luca, author.
by
Ravichandiran, Sudharsan, author.
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Hands-on reinforcement learning with python : master reinforcement learning and deep reinforcement
by
Palanisamy, Praveen, author.
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reinforcement learning / Palanisamy, Praveen, author.
by
Lanham, Micheal, author.
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algorithms such as deep reinforcement learning for games / Lanham, Micheal, author.
by
Bakker, Indra den, author.
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, reinforcement learning, and transfer learning using Python / Bakker, Indra den, author.
by
Busoniu, Lucian.
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Reinforcement learning and dynamic programming using function approximators Busoniu, Lucian.
by
Haarnoja, Tuomas, author.
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Acquiring Diverse Robot Skills via Maximum Entropy Deep Reinforcement Learning / Haarnoja, Tuomas
by
Mo, Kaixiang, author.
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Transfer Reinforcement Learning for Task-Oriented Dialogue Systems / Mo, Kaixiang, author.
by
Patel, Sahil S., author.
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A Deep Reinforcement Learning Approach to the Portfolio Management Problem / Patel, Sahil S
by
Encapera, Angelo Michael, author.
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A New Reinforcement Learning Algorithm with Fixed Exploration for Semi-Markov Decision Processes /
by
Jardine, P. Travis, author.
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A reinforcement learning approach to predictive control design: Autonomous vehicle applications /
by
Lawhead, Ryan Jacob, author.
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A Bounded Actor-Critic Algorithm for Reinforcement Learning / Lawhead, Ryan Jacob, author.
by
Stachenfeld, Kimberly, author.
Format:
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Learning Neural Representations that Support Efficient Reinforcement Learning / Stachenfeld
by
Hierck, Tom.
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7 key components for a positive learning environment -- Common expectations -- Targeted instruction
by
Wickens, J. (Jeff)
ScienceDirect http://www.sciencedirect.com/science/book/9780080422787
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striatum. 7.2. Reinforcement learning in neural nets. 7.3. The striatum and reward-mediated learning
by
Guida, Tony, 1979- author.
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-Vector-Machine Based Global Tactical Asset Allocation Chapter 12: Reinforcement learning in finance Chapter 13: Deep
by
Santacruz, Carol, author.
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suggested that video modeling was an effective strategy to indicate contingencies of reinforcement resulting
by
Mackintosh, N. J. (Nicholas John), 1935-
ScienceDirect https://www.sciencedirect.com/science/book/9780080571690
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/ Discrimination and categorization / The neural basis of learning with particular reference to the role of
by
Reese, Hayne Waring, 1931-
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, Marcia S. Scott -- Two Aspects of Experience in Ontogeny: Development and Learning / Hans G. Furth -- The
by
Reese, Hayne Waring, 1931-
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-- Conditional Responding as a Paradigm for Observational, Imitative Learning and Vicarious-Reinforcement /Jacob
by
Lipsitt, Lewis Paeff, 1929-
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-- Social Reinforcement of Children's Behavior / Harold W. Stevenson -- Delayed Reinforcement Effects
by
Lu, Zhongqi, author.
Format:
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mechanism of reinforcement learning models. The transfer learning approach is driven by the rich source
by
Kulkarni, Parag. author.
Format:
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-- Reinforcement and Deep Reinforcement Machine Learning -- Creative Machine Learning -- Co-operative and
by
Gottfried, Jay A.
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learning, and the motivational control of goal-directed action / Bernard W. Balleine -- Reward predictions
by
Donahoe, John W., 1932-
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: Perceiving -- Part four: Behaving -- Part Five: Reinforcement Learning -- Part Six: Complex Behavior
by
Reese, Hayne Waring, 1931-
Format:
Alıntı:
Model of Human Learning / Barry Gholson, Harry Beilin -- The Development of Discrimination Learning: A
by
Pfeiffer, Carl Curt.
ScienceDirect http://www.sciencedirect.com/science/book/9780123668189
Format:
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Attentional Deficits Modulated by Arousal; Appendix; References; Chapter 7. Marihuana, Learning, and Memory; I
by
Bower, Gordon H.
Format:
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reinforcement: paradigms for experimental analysis of response shaping / John R. Platt -- Prolonged rewarding
by
Weikert, Donna Elizabeth, author.
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strong factor was reinforcement of strategies integrating content and focusing on reading level of the
by
Panchpor, Aishwarya A., author.
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Learning along with Simultaneous Localization and Mapping (SLAM) to find a path and map the unknown dynamic
by
Mcdougle, Samuel David, author.
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systems during human reinforcement and sensorimotor learning.
by
Zhang, Chiyuan, author.
Format:
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language processing, and reinforcement learning. In this thesis, we will investigate deep learning from a
by
Zhu, Qinyun, author.
Format:
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solved by reinforcement learning. The experimental results suggest that both approaches outperform their
by
Duan, Jiajun, author. (orcid)0000-0001-7041-0978
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. Besides, a reinforcement learning method is designed to counteract the unavoidable network imperfections
by
Szewczyk, Roman. editor.
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Matteucci Effect Measurements -- Utilization of Deep Reinforcement Learning for saccadic-based object visual
by
Beyerer, Jürgen. editor.
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A Concept for the Application of Reinforcement Learning in the Optimization of CAM-Generated Tool
by
Bai, Quan. editor.
Format:
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.Associative Memory-based Approach to Multi-task Reinforcement Learning under Stochastic Environments -- 12
by
Jokinen, Kristiina. editor.
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Reinforcement Learning Dialogue System -- Breakdown Detector for Chat-oriented Dialogue -- User Involvement in
by
Rimanoczy, Isabel, 1956-, author.
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: repetition and reinforcement -- 15. Principle 10: learning facilitator --
by
Rajagopal, Karthikeyan, author.
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Motivated by the limitations of the current reinforcement learning and optimal control techniques
by
Mars, Rogier B.
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/ Ullsperger -- Contributions of ventromedial prefrontal and frontal polar cortex to reinforcement learning and
by
Borsini, Franco, editor.
ScienceDirect http://www.sciencedirect.com/science/book/9780123859020
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. -- Behavioral and neurochemical pharmacology of 5-HT6 receptors related to reward and reinforcement. / Gaetano
by
Ågmo, Anders.
ScienceDirect http://www.sciencedirect.com/science/book/9780123705907
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. -- Endocrine control of sexual behavior. -- Neural control of sexual behavior. -- Learning and sex: Sexual
by
Bower, Gordon H.
Format:
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. Summary and Conclusions; References; CHAPTER 7. TEMPORAL LEARNING; I. Introduction; II. Experimental
by
Bower, Gordon H.
Format:
Alıntı:
. Constraints on Positive Reinforcement; III. Constraints on Punishment; IV. Constraints on Avoidance Learning
by
Berlyne, D. E., editor.
ScienceDirect http://www.sciencedirect.com/science/book/9780120925506
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and Thelematoscopic Pneumatology?; References; CHAPTER 2. Brain Mechanisms of Reinforcement Learning
by
Bower, Gordon H.
Format:
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-TIME REINFORCEMENT1; I. Schedules of Reinforcement and Behavior; II. Need for Theory; III. Kinds of Theories; IV
by
Spence, Kenneth W.
Format:
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. Summary and Concluding Comments; References; CHAPTER 2. A SEQUENTIAL HYPOTHESIS OF INSTRUMENTAL LEARNING
by
Wang, De, author.
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defense in computer security, policy distillation in reinforcement learning, etc. Those tasks would
by
Tsiakas, Konstantinos, author.
Format:
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Learning (RL) is an appropriate machine learning paradigm for solving sequential decision making problems
by
Baniya, Abiral, author.
Format:
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performance. The reinforcement learning (Q-learning), a computational algorithm for optimization of treatment
by
Rastegardoost, Nazanin, author. (orcid)0000-0002-2931-4017
Format:
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approach, LTE-U uses carrier sensing along with the modelfree and goal-directed reinforcement learning
by
Gentry, Ronny Nicole, author.
Format:
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. Rewards and punishments both drive behavior through reinforcement learning mechanisms and sometimes occur
by
Li, Teng, author.
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Reinforcement Learning (DRL) provides a promising approach for enabling effective model-free control. The
by
Artzi, Lauren, author.
Format:
Alıntı:
small additional positive effects for the added reinforcement in the reinforcement plus condition (d=.24
by
Li, Ji, author.
Format:
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together with the reinforcement learning method to solve one complicated control problem, i.e., cloud
by
Sweidan, Husam I., author. (orcid)0000-0003-4771-9680
Format:
Alıntı:
square position error. The last scenario involves the use of inverse reinforcement learning (IRL) to
by
Le, Tuc Viet, author.
Format:
Alıntı:
, hidden Markov model, revealed preference learning and (inverse) reinforcement learning in the integrated
by
Wang, Yue. editor.
Format:
Alıntı:
Standing Balance Control and Reinforcement -- A Learning Algorithm to Select Consistent Reactions to Human
by
Banerjee, Rahul, editor.
ScienceDirect https://www.sciencedirect.com/science/bookseries/00796123/168
ScienceDirect https://www.sciencedirect.com/science/book/9780444530509
ScienceDirect https://www.sciencedirect.com/science/bookseries/00796123
ScienceDirect https://www.sciencedirect.com/science/publication?issn=00796123&volume=168
ScienceDirect https://www.sciencedirect.com/science/book/9780444530509
ScienceDirect https://www.sciencedirect.com/science/bookseries/00796123
ScienceDirect https://www.sciencedirect.com/science/publication?issn=00796123&volume=168
Format:
Alıntı:
-cellular signaling pathways involved in reinforcement learning at the striatum / S.M. Wanjerkhede, R.S. Bapi
by
Brown, Daniel, Dr.
ScienceDirect https://www.sciencedirect.com/science/book/9781843340799
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; Artificial neural networks; Bayesian inference; Rules-based systems; Reinforcement learning; Summary; Chapter
by
Omidvar, Omid.
ScienceDirect http://www.sciencedirect.com/science/book/9780125264303
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Introduction : neural networks and automatic control / David L. Elliott -- Reinforcement learning
by
International Conference on Machine Learning (12th : 1995 : Tahoe City, Calif.)
ScienceDirect http://www.sciencedirect.com/science/book/9781558603776
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AcknowledgementReferences; Chapter 4. Residual Algorithms: Reinforcement Learning with Function
by
Touretzky, David S.
ScienceDirect https://www.sciencedirect.com/science/book/9781483214481
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4 Two Interacting Fully Recurrent Self-Supervised Learning Networks for Reinforcement Learning5 An
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Symposium on the Psychology of Human Learning (1962 : University of Michigan)
ScienceDirect http://www.sciencedirect.com/science/book/9781483231457
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. Discussions focus on classical and instrumental conditioning and the nature of reinforcement; comparability of
by
Tabatabaei, Hoda Sadat Ayatollahi, author.
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Process (MDP) and optimized using reinforcement learning. I define the reward function based on the
by
Poznyak, Tatyana.
Format:
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-- 3.1.3 Recurrent neural network -- 3.1.4 Learning ability and reinforcement learning -- 3.1.5 Why
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