###Aliengo RL### Training and visualization of the Aliengo quadruped walking using Soft Actor-Critic (SAC) in the Ant-v5 environment (Gymnasium/MuJoCo). #Installation#

Clone the repository: bash

git clone https://github.com/pr0tos/aliengo_rl.git
cd aliengo_rl

Create a Conda environment: bash

conda env create -f environment.yml
conda activate aliengo_rl
pip install --upgrade anyio

#Usage#

Train a new SAC model: bash

python aliengo_train.py --use_wandb

Saves model to aliengo_models/aliengo_policy.pth. Logs metrics to WandB (if enabled).

#Visualization# Visualize the trained policy: bash

python viz_aliengo_walk.py

#Known Issues and Fixes#

1. CUDA Initialization Error Error:

   UserWarning: CUDA initialization: CUDA unknown error - this may be due to an incorrectly set up environment, e.g. changing env variable CUDA_VISIBLE_DEVICES after program start. Setting the available devices to be zero. (Triggered internally at /opt/conda/conda-bld/pytorch_1724789115765/work/c10/cuda/CUDAFunctions.cpp:108.)
   return torch._C._cuda_getDeviceCount() > 0

Solution:

sudo rmmod nvidia_uvm
sudo modprobe nvidia_uvm

2. GLFW/OpenGL Configuration Issues Error:

GLFWError: (65542) b'GLX: No GLXFBConfigs returned'  
GLFWError: (65545) b'GLX: Failed to find a suitable GLXFBConfig'  
Assertion `window != NULL' failed.

Solution:

export LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libstdc++.so.6