Weighted QMIX: Expanding Monotonic Value Function Factorisation

Last update: Dec 29, 2022

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Overview

Weighted QMIX: Expanding Monotonic Value Function Factorisation (NeurIPS 2020)

Based on PyMARL (https://github.com/oxwhirl/pymarl/). Please refer to that repo for more documentation.

This repo contains the cleaned-up code that was used in "Weighted QMIX: Expanding Monotonic Value Function Factorisation" (https://arxiv.org/abs/2006.10800).

Included in this repo

In particular implementations for:

OW-QMIX
CW-QMIX
Versions of DDPG & SAC used in the paper

We thank the authors of "QPLEX: Duplex Dueling Multi-Agent Q-Learning" (https://arxiv.org/abs/2008.01062) for their implementation of QPLEX (https://github.com/wjh720/QPLEX/), whose implementation we used. The exact implementation we used is included in this repo.

Note that in the repository the naming of certain hyper-parameters and concepts is a little different to the paper:

α in the paper is w in the code
Optimistic Weighting (OW) is referred to as hysteretic_qmix

For all SMAC experiments we used SC2.4.6.2.69232 (not SC2.4.10). The underlying dynamics are sufficiently different that you cannot compare runs across the 2 versions!

The install_sc2.sh script will install SC2.4.6.2.69232.

Running experiments

The config files (src/config/algs/*.yaml) contain default hyper-parameters for the respective algorithms. These were changed when running the experiments for the paper (epsilon_anneal_time = 1000000 for the robustness to exploration experiments, and w=0.1 for the predator prey punishment experiments for instance). Please see the Appendix of the paper for the exact hyper-parameters used.

Set central_mixer=atten to get the modified mixing network architecture that was used for the final experiment on corridor in the paper.

As an example, to run the OW-QMIX on 3s5z with epsilon annealed over 1mil timesteps using docker:

bash run.sh $GPU python3 src/main.py --config=ow_qmix --env-config=sc2 with env_args.map_name=3s5z w=0.5 epsilon_anneal_time=1000000

Citing

Bibtex:

@inproceedings{rashid2020weighted,
  title={Weighted QMIX: Expanding Monotonic Value Function Factorisation},
  author={Rashid, Tabish and Farquhar, Gregory and Peng, Bei and Whiteson, Shimon},
  booktitle={Advances in Neural Information Processing Systems},
  year={2020}
}

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Comments

simple question regarding stag-hunt rendering

Hello,

First, thank you for sharing your code and research, it is really helpful.

During the research, I become curious about how the agents act during training on stag-hunt environment. But it seems the visualization part on stag-hunt in the uploaded code is not implemented. Hence, I was wondering if there is any update on rendering part? If so, could you share the update?

opened by HyunghoNa 0
A question about the proof

I am reading about the WQMIX, but I am not sure about the proof in the appendix:

Why the $Q_{tot}^\prime \in Q^{mix}$ ? How can I check a construction that in the QMIX family or not? Would u like to help me figure it out?

opened by Jarvis-K 0
TypeError: run() missing 1 required positional argument: 'pymongo_client'

Hi when I run the example "" I get the following error with pymongo. Any idea on how to fix this?

Thanks in advance

:/pymarl# python3 src/main.py --config=qmix --env-config=sc2 with env_args.map_name=2s3z pygame 2.0.0 (SDL 2.0.12, python 3.5.2) Hello from the pygame community. https://www.pygame.org/contribute.html src/main.py:79: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. config_dict = yaml.load(f) src/main.py:49: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. config_dict = yaml.load(f) Traceback (most recent call last): File "src/main.py", line 85, in alg_config = _get_config(params, "--config", "algs") File "src/main.py", line 47, in _get_config with open(os.path.join(os.path.dirname(file), "config", subfolder, "{}.yaml".format(config_name)), "r") as f: FileNotFoundError: [Errno 2] No such file or directory: 'src/config/algs/qmix.yaml' root@6c7269d7eab6:/pymarl# python3 src/main.py --config=ow_qmix --env-config=sc2 with env_args.map_name=3s5z w=0.5 epsilon_anneal_time=1000000 pygame 2.0.0 (SDL 2.0.12, python 3.5.2) Hello from the pygame community. https://www.pygame.org/contribute.html src/main.py:79: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. config_dict = yaml.load(f) src/main.py:49: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details. config_dict = yaml.load(f) [INFO 18:08:50] root Saving to FileStorageObserver in results/sacred. [DEBUG 18:08:50] pymarl Using capture mode "fd" [INFO 18:08:50] pymarl Running command 'my_main' [INFO 18:08:50] pymarl Started run with ID "1" [DEBUG 18:08:50] my_main Started [ERROR 18:08:50] pymarl Failed after 0:00:00! Traceback (most recent calls WITHOUT Sacred internals): File "src/main.py", line 35, in my_main run(_run, config, _log) TypeError: run() missing 1 required positional argument: 'pymongo_client'

opened by lcassano 10

Owner

whirl

Whiteson Research Lab

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Weighted QMIX: Expanding Monotonic Value Function Factorisation

Related tags

Overview

Weighted QMIX: Expanding Monotonic Value Function Factorisation (NeurIPS 2020)

Included in this repo

For all SMAC experiments we used SC2.4.6.2.69232 (not SC2.4.10). The underlying dynamics are sufficiently different that you cannot compare runs across the 2 versions!

Running experiments

Citing

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Comments

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A question about the proof

TypeError: run() missing 1 required positional argument: 'pymongo_client'

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