https://github.com/ardamavi/Game-Bot
Artificial intelligence learn playing any game with watching you.
https://github.com/ardamavi/Game-Bot
artificial-intelligence deep-learning keras tensorflow
Last synced: about 1 year ago
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Artificial intelligence learn playing any game with watching you.
- Host: GitHub
- URL: https://github.com/ardamavi/Game-Bot
- Owner: ardamavi
- License: apache-2.0
- Created: 2017-06-23T12:14:22.000Z (almost 9 years ago)
- Default Branch: master
- Last Pushed: 2023-05-27T19:53:45.000Z (about 3 years ago)
- Last Synced: 2025-03-17T12:55:17.467Z (over 1 year ago)
- Topics: artificial-intelligence, deep-learning, keras, tensorflow
- Language: Python
- Homepage:
- Size: 23.4 KB
- Stars: 484
- Watchers: 29
- Forks: 127
- Open Issues: 26
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Metadata Files:
- Readme: README.md
- License: LICENSE
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- awesome - ardamavi/Game-Bot - Artificial intelligence learn playing any game with watching you. (Python)
README
# Game Bot
### By Arda Mavi
Artificial intelligence that learns to play any game by watching you.
## How does this work?
- First: Run program and play any game for a little bit.
- Second: Run program and watch the artificial intelligence play the game.
## How does it work behind the scenes?
When you run the training program, the program listens for your keyboard and mouse moving, then it saves those movements.
Artificial intelligence learn: When I push any button?
And when you run the program, it plays the game just like you!
## But how does it learn?
##### Magic! (just joking)
With deep learning.
Deep Learning is a subfield of machine learning with neural networks inspired by the structure of the brains artificial neural networks.
### Playing with Artificial Intelligence:
1. Open your desired game (If you have already trained the artificial intelligence).
2. Run `python3 ai.py` command in terminal.
### Creating Training Dataset:
1. Run `python3 create_dataset.py` command in terminal.
2. Play your desired game.
3. Stop `create_dataset` program with `Cntrl-C` in terminal.
### Model Training:
`python3 train.py`
### Using TensorBoard:
`tensorboard --logdir=Data/Checkpoints/logs`
### Important Notes:
- Tested in Python version 3.6.0
- Install necessary modules with `sudo pip3 install -r requirements.txt` command.
## WINDOWS Installation:
- Install Python 3.6.0 : https://www.python.org/downloads/release/python-360/
- Run CMD and Input Command `pip3 install -r requirements.txt`
### This project is still being worked on ...