aboudykreidieh / h-baselines Goto Github PK
View Code? Open in Web Editor NEWA repository of high-performing hierarchical reinforcement learning models and algorithms.
License: MIT License
A repository of high-performing hierarchical reinforcement learning models and algorithms.
License: MIT License
Installing the repository on Linux (as detailed in the README) gives me the following error when executing pip install -e .
:
ERROR: Cannot install h-baselines because these package versions have conflicting dependencies.
The conflict is caused by:
gym 0.14.0 depends on cloudpickle~=1.2.0
tensorflow-probability 0.8.0 depends on cloudpickle==1.1.1
To fix this you could try to:
1. loosen the range of package versions you've specified
2. remove package versions to allow pip attempt to solve the dependency conflict
ERROR: ResolutionImpossible: for help visit https://pip.pypa.io/en/latest/user_guide/#fixing-conflicting-dependencies
Is this a known issue, or have I gone wrong at some point?
Best,
Markus
Original paper: https://arxiv.org/pdf/1703.01161.pdf
setup.py
environment.yaml
fileIn AntMaze env, if 'evaluate' is true then there will be 3 AntMaze env with different context goal. Is the use of 'evaluate' testing the performance of agent instead of training?
Maybe there are some mistakes when using envs from "efficient-hrl", I guess maybe it mainly for compatible problem?
Error information:
AttributeError: 'AntFall' object has no attribute 'wrapped_env'
Original paper: https://arxiv.org/pdf/1805.08296.pdf
It appears the implementations here currently don't support using Gym environments with Discrete action spaces. For example, the following code produces an error:
$ python -c 'from hbaselines.algorithms import RLAlgorithm; from hbaselines.fcnet.sac import FeedForwardPolicy; alg=RLAlgorithm(policy=FeedForwardPolicy, env="CartPole-v0", total_steps=1000000)'
WARNING:tensorflow:
The TensorFlow contrib module will not be included in TensorFlow 2.0.
For more information, please see:
* https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md
* https://github.com/tensorflow/addons
* https://github.com/tensorflow/io (for I/O related ops)
If you depend on functionality not listed there, please file an issue.
pygame 2.0.1 (SDL 2.0.14, Python 3.7.10)
Hello from the pygame community. https://www.pygame.org/contribute.html
2021-09-16 13:25:32.015754: I tensorflow/core/platform/cpu_feature_guard.cc:142] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA
2021-09-16 13:25:32.031343: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2599880000 Hz
2021-09-16 13:25:32.031693: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x56147bad4370 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2021-09-16 13:25:32.031734: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/home/jlilly7/Code/h-baselines-d/hbaselines/algorithms/rl_algorithm.py", line 581, in __init__
self.trainable_vars = self.setup_model()
File "/home/jlilly7/Code/h-baselines-d/hbaselines/algorithms/rl_algorithm.py", line 689, in setup_model
**self.policy_kwargs
File "/home/jlilly7/Code/h-baselines-d/hbaselines/fcnet/sac.py", line 205, in __init__
self._ac_means = 0.5 * (ac_space.high + ac_space.low)
AttributeError: 'Discrete' object has no attribute 'high'
Given how broadly applicable discrete action spaces are, it would be good for this repo to support them. Alternatively, if I've misunderstood and done something wrong, please let me know.
I'm currently attempting to make adjustments for discrete environments in a fork; possibly a pull request could come out of this if it works well, but no promises yet.
Hello. When I use run_hrl to run "python run_hrl "HalfCheeth-v2" ", a problem comes with action=nan. It occures in self._policy() of ri_algorithm.py. Of course, run_fcnet is well. How can I deal with it?
Original paper: https://arxiv.org/pdf/1804.02808.pdf
Original paper: https://arxiv.org/pdf/1610.05182.pdf
Hi,
Sorry I'm reposing this from flow repo, kinda in a desperate rushing condition for tests.
I've tried this by just importing the MultiFeedForwardPolicy
in run_eval.py, apparently doesn't work and require more work.
Any plan to deploy this soon?
Thanks.
Original paper: https://arxiv.org/pdf/1609.05140.pdf
Tasks:
I used h-baselines to reproduce HIRO and HAC. But there are two problems:
The link in README.md seems invalid.
And are there any docs to describe how to reproduce benchmark results?
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.