projects:bildungskarenz:hexagon
Table of Contents
SuperHexagon AI
- Video of the Game: https://www.youtube.com/watch?v=5mDjFdetU28
- Video of an algorithm based Player https://www.youtube.com/watch?v=EUxRYix2aaM
Goal
Let the computer play the game.
- Vision-Based, the only input it the screen image. The game is controlled via keyboard emulation.
- Use a deep learning framework to train an artificial player.
- Compare different approaches. In terms of leaning rate and success.
- Supervised Learning
- Reinforcement Learning
- Algorithmic Approach
- Compare the influence of preprocessing steps e.g.
- Raw image
- Polar Transformation
- Rotated (player has fixed position)
Needed Steps
- Create/Extend the current test framework.
- Automatically start the game
- Evaluate the results
- Compare different Implementations
- Robustness
- Select a suitable machine learning framework
- Collect data from human player and algorithm-based implementation
- Train a learning model
- Improve on debugging and Analytics tools.
- Iterate on the design
- Collect and analyze the Result
projects/bildungskarenz/hexagon.txt · Last modified: 2020/08/13 18:41 by wasle