Authors: Zhe Ren, Xinghua Li, Yinbin Miao, Zhuowen Li, Zihao Wang, Ximeng Liu, Robert H. Deng Keywords: UAVs, Gossip Protocol, Sparse Rewards, Partially Observable Markov Decision Process, Reinforcement Learning
- Python
- NS-3 (version == 3.25)
The Proof-of-concept is made up of two parts as follows:
- UAVNET environment simulated using NS-3
- Deep Reinforcement Learning code
Among them, the UAVNET environment code is GossipEnvironment.py
, while others compose the deep reinforcement learning code.
Note: The NS-3 simulation environment with python support needs to be installed, more details see: ns-3 | a discrete-event network simulator for internet systems (nsnam.org)
Python Dependencies:
- pytorch
- gym
- tqdm
- After alter the train parameters, to train a new model:
$ python branching_dqn.py
- Using a pre-trained model:
$ python enjoy.py