Zhenghao Peng

This assertion error shows that the input observation is not correct. 91 is the shape of your obs and 92 is what CoPO network expecting. Obviously, this is because you...

Hi @6Lackiu Since I am preparing to release evaluation result, I have refactored the evaluation script but not yet merge. https://github.com/decisionforce/CoPO/pull/24 You can take a look on this PR, where...

Just FYI, I finished benchmarking the results of various MARL algorithms in MetaDrive MARL environments. Please kindly refer to this page: https://github.com/metadriverse/metadrive-benchmark/tree/main/MARL And I also upload latest trained models so...

This is due to the changes of the environments. MetaDrive multiagent benchmark became much harder! I will update models and exp results soon! Best regards! Peng Zhenghao (彭正皓) > 在...

Hi Yoonsoo, Finally, I finished benchmarking the results of various MARL algorithms in MetaDrive MARL environments. Please kindly refer to this page: https://github.com/metadriverse/metadrive-benchmark/tree/main/MARL And I also upload latest trained models...

Hi @Lucky-Lance , I am preparing a torch + RLLib version of CoPO and will release soon (probably next week).

Hi @shile1998 !! Sorry for late reply! I believe the performance discrepancy is due to the change of the MetaDrive environment. Therefore I launch a new project to rerun all...

As I updated last month, the result is in https://github.com/metadriverse/metadrive-benchmark/tree/main/MARL Do you have any question?

> Hi Zhenghao, > I trained the intersection using torch copo (train_copo.py) and tried to evaluate the performance using copo_code/new_vis.py. > However, it gives unpickled = pickle.loads(data) TypeError: an integer...

Just for your information, the torch version of CoPO is implemented here: https://github.com/decisionforce/CoPO/tree/main/copo_code/copo/torch_copo with ray==2.2.0