Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control
Latest Publications

TOTAL DOCUMENTS

(FIVE YEARS 22)

H-INDEX

(FIVE YEARS 0)

Published By Springer International Publishing

9783030609894, 9783030609900

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Computational Intelligence in Uncertainty Quantification for Learning Control and Differential Games

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_13 ◽

2021 ◽

pp. 385-418

Author(s):

Mushuang Liu ◽

Yan Wan ◽

Zongli Lin ◽

Frank L. Lewis ◽

Junfei Xie ◽

...

Keyword(s):

Uncertainty Quantification ◽

Differential Games ◽

Computational Intelligence ◽

Learning Control

Download Full-text

Adaptive Dynamic Programming in the Hamiltonian-Driven Framework

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_7 ◽

2021 ◽

pp. 189-214

Author(s):

Yongliang Yang ◽

Donald C. Wunsch II ◽

Yixin Yin

Keyword(s):

Dynamic Programming ◽

Adaptive Dynamic Programming ◽

Adaptive Dynamic

Download Full-text

A Hybrid Dynamical Systems Perspective on Reinforcement Learning for Cyber-Physical Systems: Vistas, Open Problems, and Challenges

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_24 ◽

2021 ◽

pp. 727-762

Author(s):

Jorge I. Poveda ◽

Andrew R. Teel

Keyword(s):

Reinforcement Learning ◽

Dynamical Systems ◽

Cyber Physical Systems ◽

Hybrid Dynamical Systems ◽

Open Problems ◽

Physical Systems ◽

Systems Perspective

Download Full-text

A Top-Down Approach to Attain Decentralized Multi-agents

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_14 ◽

2021 ◽

pp. 419-431

Author(s):

Alex Tong Lin ◽

Guido Montúfar ◽

Stanley J. Osher

Keyword(s):

Top Down ◽

Multi Agents

Download Full-text

Trading Utility and Uncertainty: Applying the Value of Information to Resolve the Exploration–Exploitation Dilemma in Reinforcement Learning

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_19 ◽

2021 ◽

pp. 557-610

Author(s):

Isaac J. Sledge ◽

José C. Príncipe

Keyword(s):

Reinforcement Learning ◽

Value Of Information ◽

Exploration Exploitation

Download Full-text

The Role of Systems Biology, Neuroscience, and Thermodynamics in Network Control and Learning

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_25 ◽

2021 ◽

pp. 763-817

Author(s):

Wassim M. Haddad

Keyword(s):

Systems Biology ◽

Network Control

Download Full-text

Quantum Amplitude Amplification for Reinforcement Learning

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_26 ◽

2021 ◽

pp. 819-833

Author(s):

K. Rajagopal ◽

Q. Zhang ◽

S. N. Balakrishnan ◽

P. Fakhari ◽

J. R. Busemeyer

Keyword(s):

Reinforcement Learning ◽

Quantum Amplitude ◽

Amplitude Amplification

Download Full-text

Dissipativity-Based Verification for Autonomous Systems in Adversarial Environments

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_10 ◽

2021 ◽

pp. 273-291

Author(s):

Aris Kanellopoulos ◽

Kyriakos G. Vamvoudakis ◽

Vijay Gupta ◽

Panos Antsaklis

Keyword(s):

Autonomous Systems ◽

Adversarial Environments

Download Full-text

Optimal Adaptive Control of Partially Uncertain Linear Continuous-Time Systems with State Delay

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_9 ◽

2021 ◽

pp. 243-272

Author(s):

Rohollah Moghadam ◽

S. Jagannathan ◽

Vignesh Narayanan ◽

Krishnan Raghavan

Keyword(s):

Adaptive Control ◽

Continuous Time ◽

State Delay ◽

Continuous Time Systems ◽

Time Systems

Download Full-text

What May Lie Ahead in Reinforcement Learning

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control ◽

10.1007/978-3-030-60990-0_1 ◽

2021 ◽

pp. 3-5

Author(s):

Derya Cansever

Keyword(s):

Reinforcement Learning

Download Full-text

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and ControlLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer International Publishing

Computational Intelligence in Uncertainty Quantification for Learning Control and Differential Games

Adaptive Dynamic Programming in the Hamiltonian-Driven Framework

A Hybrid Dynamical Systems Perspective on Reinforcement Learning for Cyber-Physical Systems: Vistas, Open Problems, and Challenges

A Top-Down Approach to Attain Decentralized Multi-agents

Trading Utility and Uncertainty: Applying the Value of Information to Resolve the Exploration–Exploitation Dilemma in Reinforcement Learning

The Role of Systems Biology, Neuroscience, and Thermodynamics in Network Control and Learning

Quantum Amplitude Amplification for Reinforcement Learning

Dissipativity-Based Verification for Autonomous Systems in Adversarial Environments

Optimal Adaptive Control of Partially Uncertain Linear Continuous-Time Systems with State Delay

What May Lie Ahead in Reinforcement Learning

Handbook of Reinforcement Learning and Control - Studies in Systems, Decision and Control
Latest Publications