File size: 1,565 Bytes
5ece54f 3839868 5ece54f 2cf1f2f 5ece54f 3f83bfd 4b657b6 3f83bfd 4b657b6 3f83bfd |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 |
---
tags:
- SuperMarioBros-v0
- RND
- CNN
- reinforcement-learning
- custom-implementation
- atari
- SuperMarioBros-v0
model-index:
- name: RND-SuperMarioBros-v0
results:
- task:
type: reinforcement-learning
name: reinforcement-learning
dataset:
name: SuperMarioBros-v0
type: SuperMarioBros-v0
metrics:
- type: mean_reward
value: 2502.70 +/- 418.86
name: mean_reward
verified: false
---
# **RND with CNN** Agent playing **SuperMarioBros-v0**
This is a trained model of a **RND-CNN** agent playing **SuperMarioBros-v0** .
To learn to use this model and train yours check this notebook on kaggle: https://www.kaggle.com/code/syedjarullahhisham/drl-extra-personal-unit-5-rnd-super-mario-bros
## Codes
Github repos(Give a star if found useful):
* https://github.com/hishamcse/DRL-Renegades-Game-Bots
* https://github.com/hishamcse/Advanced-DRL-Renegades-Game-Bots
Kaggle Notebook:
* https://www.kaggle.com/code/syedjarullahhisham/drl-extra-personal-unit-5-rnd-super-mario-bros
* https://www.kaggle.com/code/syedjarullahhisham/drl-extra-personal-unit-5-rnd-montezuma-mario-bros
# HyperParameters:
```
"trainmethod": "RND",
"envid": "SuperMarioBros-v0",
"maxstepperepisode": 18000,
"learningrate": 0.0001,
"numenv": 128,
"numstep": 128,
"gamma": 0.999,
"intgamma": 0.99,
"lambda": 0.95,
"usegae": true,
"clipgradnorm": 0.5,
"entropy": 0.001,
"epoch": 4,
"minibatch": 4,
"ppoeps": 0.1,
"extcoef": 5.0,
"intcoef": 1.0,
"stickyaction": true,
"actionprob": 0.25,
"lifedone": false,
"obsnormstep": 50
``` |