Hands-On Deep Learning for Games
Leverage the power of neural networks and reinforcement learning to build intelligent games
Published on 23. September 2024
392 pages
978-1-78899-876-5 (ISBN)
Description
No detailed description available for "Hands-On Deep Learning for Games".
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Edition
Digital original
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
US School Grade: College Graduate Student
Edition type
Digital original
File size
22,45 MB
ISBN-13
978-1-78899-876-5 (9781788998765)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
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Micheal Lanham
Hands-On Deep Learning for Games
Leverage the power of neural networks and reinforcement learning to build intelligent games
Book
03/2019
Packt Publishing
€51.80
Shipment within 3-4 weeks
Person
Lanham Micheal :
Micheal Lanham is a proven software and tech innovator with 20 years of experience. During that time, he has developed a broad range of software applications in areas such as games, graphics, web, desktop, engineering, artificial intelligence, GIS, and machine learning applications for a variety of industries as an R&D developer. At the turn of the millennium, Micheal began working with neural networks and evolutionary algorithms in game development. He was later introduced to Unity and has been an avid developer, consultant, manager, and author of multiple Unity games, graphic projects, and books ever since.
Micheal Lanham is a proven software and tech innovator with 20 years of experience. During that time, he has developed a broad range of software applications in areas such as games, graphics, web, desktop, engineering, artificial intelligence, GIS, and machine learning applications for a variety of industries as an R&D developer. At the turn of the millennium, Micheal began working with neural networks and evolutionary algorithms in game development. He was later introduced to Unity and has been an avid developer, consultant, manager, and author of multiple Unity games, graphic projects, and books ever since.
Content
Table of Contents
Deep Learning for Games
Convolutional and Recurrent Networks
GAN for Games
Building a Deep Learning Gaming Chatbot
Introducing DRL
Unity ML-Agents
Agent and the Environment
Understanding PPO
Rewards and Reinforcement Learning
Imitation and Transfer Learning
Building Multi-Agent Environments
Debugging/Testing a Game with DRL
Obstacle Tower Challenge and Beyond
Deep Learning for Games
Convolutional and Recurrent Networks
GAN for Games
Building a Deep Learning Gaming Chatbot
Introducing DRL
Unity ML-Agents
Agent and the Environment
Understanding PPO
Rewards and Reinforcement Learning
Imitation and Transfer Learning
Building Multi-Agent Environments
Debugging/Testing a Game with DRL
Obstacle Tower Challenge and Beyond
