# Visualization of Deep Reinforcement Autonomous Aerial Mobility Learning Simulations

arXiv: https://arxiv.org/abs/2102.08761 · HTML: https://mlsanity.com/paper/2102.08761/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Feb 2021.

## Built on by (most cited first, 1 of 1)

- [Tutorial on Course-of-Action (COA) Attack Search Methods in Computer Networks](https://mlsanity.com/paper/2205.13763/) (2022)

## Abstract (arXiv)

This demo abstract presents the visualization of deep reinforcement learning (DRL)-based autonomous aerial mobility simulations. In order to implement the software, Unity-RL is used and additional buildings are introduced for urban environment. On top of the implementation, DRL algorithms are used and we confirm it works well in terms of trajectory and 3D visualization.