The code for paper: 《Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Network》

Requirements

• Gym 0.15.7
• mujoco-py 2.0.2.13
• Python 3.6.13
• PyTorch 1.6.0+cpu

The code has been tested on an AMD EPYC 7742 server without using GPU.

Explanations

• ./results: the saved checkpoints and results on 10 runs
• ./CartPole-v1, HalfCheetah-v2, Swimmer-v2, or HumanoidStandup-v2: training log
• result_analyze.py: result analysis and visualization code
• ./imgs: visualization results in our paper

Run Steps

bash run.sh # Need to specify env_name(CartPole-v1, HalfCheetah-v2, Swimmer-v2, or HumanoidStandup-v2) and policy_type(SPN_Weights or SPN_Connections).