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https://github.com/neka-nat/player_zoo
Deep reinforcement learning implementations
https://github.com/neka-nat/player_zoo
a3c cem ddpg deep-q-network deep-reinforcement-learning double-dqn dueling-dqn prioritized-replay pytorch reinforcement-learning visdom
Last synced: about 1 month ago
JSON representation
Deep reinforcement learning implementations
- Host: GitHub
- URL: https://github.com/neka-nat/player_zoo
- Owner: neka-nat
- License: mit
- Created: 2018-06-24T14:05:19.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2019-08-26T15:28:36.000Z (over 5 years ago)
- Last Synced: 2024-10-14T19:42:55.306Z (3 months ago)
- Topics: a3c, cem, ddpg, deep-q-network, deep-reinforcement-learning, double-dqn, dueling-dqn, prioritized-replay, pytorch, reinforcement-learning, visdom
- Language: Python
- Homepage:
- Size: 3.41 MB
- Stars: 1
- Watchers: 4
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# player_zoo
Implementation of Reinforcement learning algorithms.
## Install
```
git clone https://github.com/neka-nat/player_zoo.git --recursive
```
Install bullet physics depended by roboschool.
```
export ROBOSCHOOL_PATH=
cd player_zoo/roboschool
git clone https://github.com/olegklimov/bullet3 -b roboschool_self_collision
mkdir -p bullet3/build
cd bullet3/build
cmake -DBUILD_SHARED_LIBS=ON -DUSE_DOUBLE_PRECISION=1 -DCMAKE_INSTALL_PREFIX:PATH=$ROBOSCHOOL_PATH/roboschool/cpp-household/bullet_local_install -DBUILD_CPU_DEMOS=OFF -DBUILD_BULLET2_DEMOS=OFF -DBUILD_EXTRAS=OFF -DBUILD_UNIT_TESTS=OFF -DBUILD_CLSOCKET=OFF -DBUILD_ENET=OFF -DBUILD_OPENGL3_DEMOS=OFF ..
make -j4
make install
cd ../../..
```
Install python packages.
```
pipenv install
```
Run a script with visdom server.
```
pipenv shell
./run.sh dqn.py
```
## Agents
### DQN
* https://arxiv.org/abs/1312.5602
### Double DQN
* https://arxiv.org/abs/1509.06461
### Dueling DQN
* https://arxiv.org/abs/1511.06581
### Prioritized Experience Replay
* https://arxiv.org/abs/1511.05952
### A3C
* https://arxiv.org/abs/1602.01783
### DDPG
* https://arxiv.org/abs/1509.02971
### TRPO
* https://arxiv.org/abs/1502.05477
### CEM
* http://learning.mpi-sws.org/mlss2016/slides/2016-MLSS-RL.pdf
## Images
### DQN
### DDPG
### A3C
