finelybook
9781788836579
Hands-On Intelligent Agents with OpenAI Gym: Your guide to developing AI agents using deep reinforcement learning
by 作者: Praveen Palanisamy
ISBN-10 书号: 178883657X
ISBN-13 书号: 9781788836579
Publisher Finelybook 出版日期: 2018-07-31
Pages: 254
Book Description
Many real-world problems can be broken down into tasks that require a series of decisions to be made or actions to be taken. The ability to solve such tasks without a machine being programmed requires a machine to be artificially intelligent and capable of learning to adapt. This book is an easy-to-follow guide to implementing learning algorithms for machine software agents in order to solve discrete or continuous sequential decision making and control tasks.
Hands-On Intelligent Agents with OpenAI Gym takes you through the process of building intelligent agent algorithms using deep reinforcement learning starting from the implementation of the building blocks for configuring,training,logging,visualizing,testing,and monitoring the agent. You will walk through the process of building intelligent agents from scratch to perform a variety of tasks. In the closing chapters,the book provides an overview of the latest learning environments and learning algorithms,along with pointers to more resources that will help you take your deep reinforcement learning skills to the next level.
Contents
1: INTRODUCTION TO INTELLIGENT AGENTS AND LEARNING ENVIRONMENTS
2: REINFORCEMENT LEARNING AND DEEP REINFORCEMENT LEARNING
3: GETTING STARTED WITH OPENAI GYM AND DEEP REINFORCEMENT LEARNING
4: EXPLORING THE GYM AND ITS FEATURES
5: IMPLEMENTING YOUR FIRST LEARNING AGENT - SOLVING THE MOUNTAIN CAR PROBLEM
6: IMPLEMENTING AN INTELLIGENT AGENT FOR OPTIMAL CONTROL USING DEEP Q-LEARNING
7: CREATING CUSTOM OPENAI GYM ENVIRONMENTS - CARLA DRIVING SIMULATOR
8: IMPLEMENTING AN INTELLIGENT - AUTONOMOUS CAR DRIVING AGENT USING DEEP ACTOR-CRITIC ALGORITHM
9: EXPLORING THE LEARNING ENVIRONMENT LANDSCAPE - ROBOSCHOOL,GYM-RETRO,STARCRAFT-II,DEEPMINDLAB
10: EXPLORING THE LEARNING ALGORITHM LANDSCAPE - DDPG (ACTOR-CRITIC),PPO (POLICY-GRADIENT),RAINBOW (VALUE-BASED)
What you will learn
Explore intelligent agents and learning environments
Understand the basics of RL and deep RL
Get started with OpenAI Gym and PyTorch for deep reinforcement learning
Discover deep Q learning agents to solve discrete optimal control tasks
Create custom learning environments for real-world problems
Apply a deep actor-critic agent to drive a car autonomously in CARLA
Use the latest learning environments and algorithms to upgrade your intelligent agent development skills
Authors
Praveen Palanisamy
Praveen Palanisamy works on developing autonomous intelligent systems. He is currently an AI researcher at General Motors R&D. He develops planning and decision-making algorithms and systems that use deep reinforcement learning for autonomous driving. Previously,he was at the Robotics Institute,Carnegie Mellon University,where he worked on autonomous navigation,including perception and AI for mobile robots. He has experience developing complete,autonomous,robotic systems from scratch.
