Reinforcement learning.

Reinforcement learningstate-of-the-art / by: (Electronic resources)

Learning motor skillsfrom algorithms to robot experiments / by: (Electronic resources)

Design of experiments for reinforcement learning by: (Electronic resources)

Reinforcement and systemic machine learning for decision making by: (Electronic resources)

Multi-agent machine learninga reinforcement approach / by: (Electronic resources)

Reinforcement learningwith Open AI, TensorFlow and Keras using Python / by: (Electronic resources)

Reinforcement learning for optimal feedback controla Lyapunov-based approach / by: (Electronic resources)

Deep reinforcement learning for wireless networks by: (Electronic resources)

Deep reinforcement learningfrontiers of artificial intelligence / by: (Electronic resources)

Towards user-centric intelligent network selection in 5G heterogeneous wireless networksa reinforcement learning perspective / by: (Electronic resources)

Applied reinforcement learning with Pythonwith OpenAI Gym, Tensorflow, and Keras / by: (Electronic resources)

Learning to playreinforcement learning and games / by: (Electronic resources)

Deep reinforcement learningfundamentals, research and applications / by: (Electronic resources)

Reinforcement learning algorithmsanalysis and applications / by: (Electronic resources)

Deep reinforcement learning with Pythonwith PyTorch, TensorFlow and OpenAI Gym / by: (Electronic resources)

Reinforcement learning aided performance optimization of feedback control systems by: (Electronic resources)

Handbook of reinforcement learning and control by: (Electronic resources)

Multi-armed banditstheory and applications to online learning in networks / by: (Electronic resources)

State-of-the-art deep learning models in Tensorflowmodern machine learning in the Google colab ecosystem / by: (Electronic resources)

Reinforcement learning for cyber-physical systems with cybersecurity case studies / by: (Electronic resources)

Reinforcement learning and stochastic optimization :a unified framework for sequential decisions / by: (Language materials, printed)

Reinforcement learning with hybrid quantum approximation in the NISQ context by: (Electronic resources)

Deep reinforcement learning by: (Electronic resources)

Control systems and reinforcement learning by: (Electronic resources)

Generic multi-agent reinforcement learning approach for flexible job-shop scheduling by: (Electronic resources)

Reinforcement learning from scratchunderstanding current approaches -- with examples in Java and Greenfoot / by: (Electronic resources)

Decision making under uncertainty and reinforcement learningtheory and algorithms / by: (Electronic resources)

Reinforcement learning for sequential decision and optimal control by: (Electronic resources)

Output feedback reinforcement learning control for linear systems by: (Electronic resources)

Reinforcement learning for financesolve problems in finance with CNN and RNN using the tensorflow library / by: (Electronic resources)

Fundamentals of reinforcement learning by: (Electronic resources)

Deep reinforcement learning processor design for mobile applications by: (Electronic resources)

Reinforcement learningoptimal feedback control with industrial applications / by: (Electronic resources)

The art of reinforcement learningfundamentals, mathematics, and implementations with Python / by: (Electronic resources)

Reinforcement learning for reconfigurable intelligent surfacesassisted wireless communication systems / by: (Electronic resources)

Integral and inverse reinforcement learning for optimal control systems and games by: (Electronic resources)

Reinforcement learningtheory and python implementation / by: (Electronic resources)

Applications of optimal transport to economics and related topics by: (Electronic resources)

Reinforcement learning for cyber operations :applications of Artificial Intelligence for penetration testing / by: (Language materials, printed)

Reinforcement learning methods in speech and language technology by: (Electronic resources)

Mathematical foundations of reinforcement learning by: (Electronic resources)