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About Deep Reinforcement Learning For Drones in 3D Realistic Environments
This document provides an overview of implementing deep reinforcement learning for drones in 3D simulated environments using Unreal Engine and Python. It describes installing the necessary platforms, including Unreal Engine, AirSim for the drone physics simulation, and a DRL Python code repository. The document then explains running the DRL code, which trains a double deep Q-network to autonomously navigate a drone in an indoor environment without collisions. Parameters like the learning rate can be modified during training using the PyGame screen interface.
Detailed Information
| Author: | ['Rahil Rehan'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 15 |
| Language: | English |
| Format: | |
| Price: | FREE |
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