Deep Reinforcement Learning Hands-On : Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / Maxim Lapan
Material type:
TextPublisher: UK Packt 2018Description: xvi,523 PagesISBN: 9781788834247Subject(s): Deep LearningDDC classification: 006.31,LAP | Item type | Current location | Home library | Shelving location | Call number | Status | Notes | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|---|---|
Reference
|
Military College of Signals (MCS) | Military College of Signals (MCS) | Reference | 006.31,LAP (Browse shelf) | Not for loan | Almirah Fresh No.43, Shelf No.1 | MCS38904 |
What is Reinforcement Learning? (Page-1), OpenAI Gym (Page-25), Deep Learning with PyTorch (Page-49), The Cross-Entropy Method (Page-77), Tabular Learning and the Bellman Equation (Page-99), Deep Q-Networks(Page-119), DQN Extensions (Page-155), Stocks Trading Using RL (Page-217), Policy Gradients – An Alternative (Page-241), The Actor-Critic Method (Page-263), Asynchronous Advantage Actor-Critic (Page-283), Chatbots Training with RL (Page-303), Web Navigation (Page-351), Continuous Action Space (Page-399), Trust Regions – TRPO, PPO, and ACKTR (Page-427), Black-Box Optimization in RL (Page-443), Beyond Model-Free – Imagination (Page-467), AlphaGo Zero (Page-491).
Click on an image to view it in the image viewer
There are no comments on this title.