by PacktPublishing · Agent Tool · ★ 397
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Hands-on Intelligent Agents with OpenAI Gym (HOIAWOG) The Book | Examples of agents you will learn to develop ::|:: Topics Covered| HOIAWOG!: Your guide to developing AI agents using deep reinforcement learning. Implement intelligent agents using PyTorch to solve classic AI problems, play console games like Atari, and perform tasks such as autonomous driving using the CARLA driving simulator. Chapter list: (Click to learn more) Chapter 1: Introduction to Intelligent Agents
| Stars | 397 |
| Forks | 157 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 61.2412062364628/100 |
| Open Issues | 4 |
| Last Updated | 2023-01-24 |
| Created | 2018-05-09 |
| Platforms | python |
| Est. Tokens | ~3375k |
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Hands-On-Intelligent-Agents-with-OpenAI-Gym is Code for Hands On Intelligent Agents with OpenAI Gym book to get started and learn to build deep reinforcement learning agents using PyTorch. It is categorized as a Agent Tool with 397 GitHub stars.
Hands-On-Intelligent-Agents-with-OpenAI-Gym is primarily written in Python. It covers topics such as actor-critic, advantage-actor-critic, carla-driving-simulator.
You can find installation instructions and usage details in the Hands-On-Intelligent-Agents-with-OpenAI-Gym GitHub repository at github.com/PacktPublishing/Hands-On-Intelligent-Agents-with-OpenAI-Gym. The project has 397 stars and 157 forks, indicating an active community.
Hands-On-Intelligent-Agents-with-OpenAI-Gym is released under the MIT license, making it free to use and modify according to the license terms.
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