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projects:bildungskarenz:hexagon

Table of Contents

SuperHexagon AI

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

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