Package: gym 0.1.0

gym: Provides Access to the OpenAI Gym API

OpenAI Gym is a open-source Python toolkit for developing and comparing reinforcement learning algorithms. This is a wrapper for the OpenAI Gym API, and enables access to an ever-growing variety of environments. For more details on OpenAI Gym, please see here: <https://github.com/openai/gym>. For more details on the OpenAI Gym API specification, please see here: <https://github.com/openai/gym-http-api>.

Authors:Paul Hendricks [aut, cre]

gym_0.1.0.tar.gz
gym_0.1.0.zip(r-4.7)gym_0.1.0.zip(r-4.6)gym_0.1.0.zip(r-4.5)
gym_0.1.0.tgz(r-4.6-any)gym_0.1.0.tgz(r-4.5-any)
gym_0.1.0.tar.gz(r-4.7-any)gym_0.1.0.tar.gz(r-4.6-any)
gym_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
gym/json (API)

# Install 'gym' in R:

install.packages('gym', repos = c('https://paulhendricks.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/paulhendricks/gym-r/issues

On CRAN:

openai-gym openai-universe reinforcement-learning

4.66 score 21 stars 44 scripts 158 downloads 19 exports 8 dependencies

Last updated from:52237a6de5. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	137
source / vignettes	OK	164
linux-release-x86_64	OK	132
macos-release-arm64	OK	91
macos-oldrel-arm64	OK	94
windows-devel	OK	69
windows-release	OK	74
windows-oldrel	OK	130
wasm-release	OK	95

Exports:create_GymClient env_action_space_contains env_action_space_info env_action_space_sample env_close env_create env_list_all env_monitor_close env_monitor_start env_observation_space_info env_reset env_step get_request GymClient parse_server_error_or_raise_for_status post_request random_discrete_agent shutdown_server upload

Dependencies:askpass curl httr jsonlite mime openssl R6 sys

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Create a GymClient instance.	create_GymClient
Evaluate whether an action is a member of an environments's action space.	env_action_space_contains
Get information (name and dimensions/bounds) of the environments's action space.	env_action_space_info
Sample an action from the environments's action space.	env_action_space_sample
Flush all monitor data to disk.	env_close
Create an instance of the specified environment.	env_create
List all environments running on the server.	env_list_all
Flush all monitor data to disk.	env_monitor_close
Start monitoring.	env_monitor_start
Get information (name and dimensions/bounds) of the environment's observation space.	env_observation_space_info
Reset the state of the environment and return an initial observation.	env_reset
Step though an environment using an action.	env_step
Submit a GET request to an OpenAI Gym server.	get_request
gym: Provides Access to the OpenAI Gym API	gym-package gym
Create a GymClient instance.	GymClient
Parse the server error or raise for status.	parse_server_error_or_raise_for_status
Submit a POST request to an OpenAI Gym server.	post_request
Represent a GymClient instance on the command line.	print.GymClient
A sample random discrete agent.	random_discrete_agent
Request a server shutdown.	shutdown_server
Flush all monitor data to disk.	upload