baselines-results's People
Forkers
tigerneil dreamstudio2015 muharremokutan nottombrown labbros alexxnica kryndex aviyashchin hedgefair benjamesbabala jdc08161063 zumbalamambo daniellsm chingyaoc universityai kaixianglin chenglongchen picopoco huoliangyu jcoreyes fuxianh kdgutier ykankaya ourobouros jcassiojr hongdazhang kiaragrouwstra zxydi1992 christopherhesse josephzizys daiviet01 jaykimbravekjh miguelmoutela liziniu afcarl wangcongrobot futurev sergiobat borishouenou muskanmahajan37 neotim mcx global19 global-localhost global19-atlassian-net classicvalues isabella232 linnetfire ayoubjadouli a-why-not-fork-repositories-good-luck joolstorrentecalo lucit21 goompean ghas-results seanpm2001 ghas-results qblockq alexanderdurrbaselines-results's Issues
Are the results reproducible?
Just wondering if the notebook files are meant to be reproducible.
If that's the case could you please provide any link to the tinkerbell dependency in https://github.com/openai/baselines-results/blob/master/acktr_ppo_acer_a2c_atari.ipynb as I'm not able to find any public package with that name.
Many thanks in advance.
Only 19 games
The evaluation results provided in the "dqn_result.pkl" only contain 19 games. Does the rest of the game's training process has no record file? If someone have, please release it.THANK YOU VERY MUCH
experiment = "atari-prior-a"
game_data = defaultdict(lambda: [])
for run_name, data in run_to_episode_data.items():
if run_name.startswith(experiment):
game = data['env_id'][:-len('NoFrameskip-v3')]
t = np.cumsum(data['episode_data']["episode_lengths"])
r = np.array(data['episode_data']["episode_rewards"])
# Ensure all mesurements after the deadline of 2e8 are thrown away
t_fltr, r_fltr = t[t < MAX_TSTEPS], r[t < MAX_TSTEPS]
game_data[game].append((t_fltr, r_fltr))
print(len(game_data.keys()))
# 19
atari50 path
I was hoping to run through the acktr_ppo_acer_a2c_atari notebook. One of the first steps is to load results from ./atari50.
Would you be able to add that path to the repository, or provide a mechanism for downloading it like the dqn_results one does?
Regrading the graphs in Param-Noise
Hey,
Is there any chance getting the code to create the graphs in the param-noise directory (as done in the jupyter notebook)? I want to use the results for comparison, but I need the data itself and not the graphs.
Thanks in advance!
It can help a lot because my computational resources are not enough for reproducing all of the deepq results by myself.
Mujoco v2 baseline results
It would be good to have Mujoco baseline results for ACKTR, A2C, TRPO , PPO and DDPG for Mujoco v2 environment update. It would be good to have benchmark results compare against.
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. ๐๐๐
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google โค๏ธ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.