# neardws/Game-Theoretic-Deep-Reinforcement-Learning

<https://repo.masters-masters.com/en/repos/neardws/Game-Theoretic-Deep-Reinforcement-Learning>

[Home](https://repo.masters-masters.com/en) › [neardws](https://repo.masters-masters.com/en/owners/neardws) › [Game-Theoretic-Deep-Reinforcement-Learning](https://repo.masters-masters.com/en/repos/neardws/Game-Theoretic-Deep-Reinforcement-Learning)

neardws/Game-Theoretic-Deep-Reinforcement-Learning has 366 stars on GitHub. Its RepoMasters card: Alpha tier. Code of Paper "Joint Task Offloading and…

| Field | Value |
| --- | --- |
| Owner | [neardws](https://repo.masters-masters.com/en/owners/neardws) |
| Stars | 366 |
| Forks | 60 |
| Language | [Python](https://repo.masters-masters.com/en/languages/python) |
| License | GPL-3.0 |
| Created | 2022 |
| Topics | deep-reinforcement-learning, noma, potential-game, resource-allocation, task-offloading, vehicular-networks |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [neardws/Game-Theoretic-Deep-Reinforcement-Learning](https://github.com/neardws/Game-Theoretic-Deep-Reinforcement-Learning) |

## Repository

Code of Paper "Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach", JSA 2022.

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.