---
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
```