Informasi Umum

Kode

23.01.766

Klasifikasi

005.133 - Special programming techniques-specific programming language

Jenis

Buku - Circulation (Dapat Dipinjam)

Subjek

Programming In Specific Programming Languages, Python,

No. Rak

2

Informasi Lainnya

Abstraksi

Deep reinforcement learning (deep RL) combines deep learning and reinforcement learning, in which artificial agents learn to solve sequential decision-making problems. In the past decade deep RL has achieved remarkable results on a range of problems, from single and multiplayer games–such as Go, Atari games, and DotA 2–to robotics.

Foundations of Deep Reinforcement Learning is an introduction to deep RL that uniquely combines both theory and implementation. It starts with intuition, then carefully explains the theory of deep RL algorithms, discusses implementations in its companion software library SLM Lab, and finishes with the practical details of getting deep RL to work. This guide is ideal for both computer science students and software engineers who are familiar with basic machine learning concepts and have a working understanding of Python. Understand each key aspect of a deep RL problem Explore policy- and value-based algorithms, including REINFORCE, SARSA, DQN, Double DQN, and Prioritized Experience Replay (PER) Delve into combined algorithms, including Actor-Critic and Proximal Policy Optimization (PPO) Understand how algorithms can be parallelized synchronously and asynchronously Run algorithms in SLM Lab and learn the practical implementation details for getting deep RL to work Explore algorithm benchmark results with tuned hyperparameters Understand how deep RL environments are designed

Koleksi & Sirkulasi

Tersedia 5 dari total 5 Koleksi

Pengarang

Nama	Laura Graesser, Wah Loon Keng
Jenis	Perorangan
Penyunting
Penerjemah

Penerbit

Nama	Addison-Wesley Professional
Kota	New York
Tahun	2019

Sirkulasi

Harga sewa	IDR 0,00
Denda harian	IDR 1.000,00
Jenis	Sirkulasi

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