Détail de l'auteur
Auteur Micheal LANHAM |
Documents disponibles écrits par cet auteur (3)
Ajouter le résultat dans votre panier Faire une suggestion Affiner la recherche
Titre : Hands-On Reinforcement Learning for Games Type de document : e-book Auteurs : Micheal LANHAM Editeur : PACKT PUBLISHING Année de publication : 2020 ISBN/ISSN/EAN : 9781839214936 Note générale : copyrighted Langues : Anglais (eng) Résumé : Explore reinforcement learning (RL) techniques to build cutting-edge games using Python libraries such as PyTorch, OpenAI Gym, and TensorFlow Key Features Get to grips with the different reinforcement and DRL algorithms for game development Learn how to implement components such as artificial agents, map and level generation, and audio generation Gain insights into cutting-edge RL research and understand how it is similar to artificial general research Book Description With the increased presence of AI in the gaming industry, developers are challenged to create highly responsive and adaptive games by integrating artificial intelligence into their projects. This book is your guide to learning how various reinforcement learning techniques and algorithms play an important role in game development with Python. Starting with the basics, this book will help you build a strong foundation in reinforcement learning for game development. Each chapter will assist you in implementing different reinforcement learning techniques, such as Markov decision processes (MDPs), Q-learning, actor-critic methods, SARSA, and deterministic policy gradient algorithms, to build logical self-learning agents. Learning these techniques will enhance your game development skills and add a variety of features to improve your game agent's productivity. As you advance, you'll understand how deep reinforcement learning (DRL) techniques can be used to devise strategies to help agents learn from their actions and build engaging games. By the end of this book, you'll be ready to apply reinforcement learning techniques to build a variety of projects and contribute to open source applications. What you will learn Understand how deep learning can be integrated into an RL agent Explore basic to advanced algorithms commonly used in game development Build agents that can learn and solve problems in all types of environments Train a Deep Q-Network (DQN) agent to solve the CartPole balancing problem Develop game AI agents by understanding the mechanism behind complex AI Integrate all the concepts learned into new projects or gaming agents Who this book is for If you're a game developer looking to implement AI techniques to build next-generation games from scratch, this book is for you. Machine learning and deep learning practitioners, and RL researchers who want to understand how to use self-learning agents in the game domain will also find this book useful. Knowledge of game development and Python programming experience are required. Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88880106 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=501746
Titre : Augmented Reality Game Development Type de document : e-book Auteurs : Micheal LANHAM Editeur : PACKT PUBLISHING Année de publication : 2017 ISBN/ISSN/EAN : 9781787122888 Note générale : copyrighted Langues : Anglais (eng) Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88842644 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=474916
Titre : Game Audio Development with Unity 5.X Type de document : e-book Auteurs : Micheal LANHAM Editeur : PACKT PUBLISHING Année de publication : 2017 ISBN/ISSN/EAN : 9781787286450 Note générale : copyrighted Langues : Anglais (eng) Nombre d'accès : Illimité En ligne : http://library.ez.neoma-bs.fr/login?url=https://www.scholarvox.com/book/88842892 Permalink : https://cataloguelibrary.neoma-bs.fr/index.php?lvl=notice_display&id=475168
LIBRARY - Campus Rouen
NEOMA Business School
pmb
-
59 Rue Taittinger, 51100 Reims
-
00 33 (0)3 26 77 46 15
Library Campus Reims
-
1 Rue du Maréchal Juin, BP 215
76825 Mont Saint Aignan cedex -
00 33 (0)2 32 82 58 26