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Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Deep Reinforcement Learning Hands-On

<span xml:lang="en">Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more</span>

Lapan, Maxim

Key FeaturesExplore deep reinforcement learning (RL), from the first principles to the latest algorithmsEvaluate high-profile RL methods, including value iteration, deep Q-networks, policy gradients, TRPO, PPO, DDPG, D4PG, evolution strategies and genetic algorithmsKeep up with the very latest industry developments, including AI-driven chatbotsBook DescriptionDeep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including Cross-entropy and policy gradients, before applying them to real-world environments.

Key FeaturesExplore deep reinforcement learning (RL), from the first principles to the latest algorithmsEvaluate...

Deep Reinforcement Learning Hands-On: Apply modern RL...

Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Format

Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more

Maxim Lapan

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