Deep Reinforcement Learning Hands-On - Second Edition
Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more - Includes Multi-Agent Methods and Advanced Exploration Techniques
Autores
Parámetros
- 826 páginas
- 29 horas de lectura
Más información sobre el libro
This updated guide delves into deep reinforcement learning, showcasing its applications in addressing intricate real-world challenges. The new edition features expanded content on multi-agent methods, discrete optimization, and the role of reinforcement learning in robotics. Additionally, it covers advanced exploration techniques, making it a comprehensive resource for both beginners and experienced practitioners seeking to deepen their understanding of this rapidly evolving field.
Compra de libros
Deep Reinforcement Learning Hands-On - Second Edition, Maxim Lapan
- Idioma
- Publicado en
- 2020
- Encuadernación
- (Tapa blanda),
- Estado del libro
- Bueno
- Precio
- 14,49 €
Métodos de pago
Nadie lo ha calificado todavía.
- Título
- Deep Reinforcement Learning Hands-On - Second Edition
- Subtítulo
- Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more - Includes Multi-Agent Methods and Advanced Exploration Techniques
- Idioma
- Inglés
- Autores
- Maxim Lapan
- Editorial
- Packt Publishing
- Publicado en
- 2020
- Formato
- Tapa blanda
- Páginas
- 826
- ISBN10
- 1838826998
- ISBN13
- 9781838826994
- Serie
- Etiquetas
- Inteligencia Artificial, Robots, Aprendizaje Automático
- Descripción
- This updated guide delves into deep reinforcement learning, showcasing its applications in addressing intricate real-world challenges. The new edition features expanded content on multi-agent methods, discrete optimization, and the role of reinforcement learning in robotics. Additionally, it covers advanced exploration techniques, making it a comprehensive resource for both beginners and experienced practitioners seeking to deepen their understanding of this rapidly evolving field.