rllab | evaluating reinforcement learning algorithms | Reinforcement Learning library

 by   rll Python Version: Current License: Non-SPDX

kandi X-RAY | rllab Summary

kandi X-RAY | rllab Summary

rllab is a Python library typically used in Artificial Intelligence, Reinforcement Learning, Deep Learning, Pytorch, Tensorflow applications. rllab has no vulnerabilities, it has build file available and it has medium support. However rllab has 21 bugs and it has a Non-SPDX License. You can download it from GitHub.

rllab is a framework for developing and evaluating reinforcement learning algorithms. It includes a wide range of continuous control tasks plus implementations of the following algorithms:. rllab is fully compatible with OpenAI Gym. See here for instructions and examples. rllab only officially supports Python 3.5+. For an older snapshot of rllab sitting on Python 2, please use the py2 branch. rllab comes with support for running reinforcement learning experiments on an EC2 cluster, and tools for visualizing the results. See the documentation for details. The main modules use Theano as the underlying framework, and we have support for TensorFlow under sandbox/rocky/tf.

            kandi-support Support

              rllab has a medium active ecosystem.
              It has 2784 star(s) with 802 fork(s). There are 172 watchers for this library.
              It had no major release in the last 6 months.
              There are 102 open issues and 81 have been closed. On average issues are closed in 94 days. There are 15 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of rllab is current.

            kandi-Quality Quality

              rllab has 21 bugs (7 blocker, 0 critical, 14 major, 0 minor) and 711 code smells.

            kandi-Security Security

              rllab has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              rllab code analysis shows 0 unresolved vulnerabilities.
              There are 14 security hotspots that need review.

            kandi-License License

              rllab has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              rllab releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              rllab saves you 16680 person hours of effort in developing the same functionality from scratch.
              It has 33149 lines of code, 3288 functions and 306 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed rllab and discovered the below as its top functions. This is intended to give you an instant insight into rllab implemented functionality, and help decide if they suit your requirements.
            • fmin function .
            • tells the program
            • Computes the eigenvalues of a QR decomposition .
            • Run EC2 .
            • Run the experiment .
            • Converts a tabular data into a table .
            • Get the plot instruction
            • Creates a kube pod from the given parameters .
            • Program entry point .
            • Plot divers .
            Get all kandi verified functions for this library.

            rllab Key Features

            No Key Features are available at this moment for rllab.

            rllab Examples and Code Snippets

            Getting Started,Local installation
            Pythondot img1Lines of Code : 22dot img1no licencesLicense : No License
            copy iconCopy
            git clone https://github.com/rll/rllab.git
            cd rllab
            git checkout b3a28992eca103cab3cb58363dd7a4bb07f250a0
            export PYTHONPATH=$(pwd):${PYTHONPATH}
            mkdir -p /tmp/mujoco_tmp && cd /tmp/mujoco_tmp
            wget -P . https://www.roboti.us/download/mjpr  
            How to run MF
            Jupyter Notebookdot img2Lines of Code : 9dot img2no licencesLicense : No License
            copy iconCopy
            python trpo_run_mf.py --seed=0 --save_trpo_run_num=1 --which_agent=4 --num_workers_trpo=4
            python trpo_run_mf.py --seed=0 --save_trpo_run_num=1 --which_agent=2 --num_workers_trpo=4
            python trpo_run_mf.py --seed=0 --save_trpo_run_num=1 --which_agent=1 -  
            How to run everything
            Jupyter Notebookdot img3Lines of Code : 9dot img3no licencesLicense : No License
            copy iconCopy
            cd scripts
            python main.py --seed=0 --run_num=1 --yaml_file='swimmer_forward'
            python mbmf.py --run_num=1 --which_agent=2
            python trpo_run_mf.py --seed=0 --save_trpo_run_num=1 --which_a  
            tensorlayer - tutorial TRPO
            Pythondot img4Lines of Code : 286dot img4License : Non-SPDX
            copy iconCopy
            Trust Region Policy Optimization (TRPO)
            PG method with a large step can collapse the policy performance,
            even with a small step can lead a large differences in policy.
            TRPO constraint the step in policy spa  

            Community Discussions


            Load model from snapshot in the Flow environment
            Asked 2019-Jun-18 at 22:14

            Repost from Flow user "ml jack":

            I'm in the process of RL training with flow and rllab. Snapshots are periodically saved. Is there a way to load these snapshot and test/re-evaluate them in the flow environment?



            Answered 2019-Jun-18 at 22:14

            From Flow Team -----

            "Yes! So if you look in the tutorials, there's a tutorial on visualizing.

            Basically, run python visualizer_rllab.py path/to/pkl and that should do it! Note: you have to specify which pkl file you want in the path as in python visualizer_rllab.py path_to_pkl/name_of_pkl_file. Advanced usage should be described in the tutorial."

            Source https://stackoverflow.com/questions/56552457


            Python- error in importing rllab
            Asked 2018-Apr-14 at 04:58

            I installed rllab successfully:



            Answered 2018-Apr-14 at 04:58

            I know this thread is quite old, but I started working on rllab lately and this is my understanding. rllab3 is a conda envrionment similar to virtual environment, as mentioned in the rllab documentation. It doesn't have the actual modules installed within it, you'd need to install it seperately.

            Source https://stackoverflow.com/questions/47123353

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install rllab

            You can download it from GitHub.
            You can use rllab like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            Documentation is available online: https://rllab.readthedocs.org/en/latest/.
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