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Training neural nets to play capture the flag Pacman variant through NeuroEvolution of Augmenting Topologies

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PacmanAI

TASKS:

  • Train and see if the agent improves. We should show at least some skill being developed for our Milestone report.
  • Easier running from command line. I could see the following being useful:
    • Train mode: Takes in a generation count for how many generations of optimization to run. Also takes flags for whether or not to load a previous agent as the base of the population or start from scratch and whether/where to save the final best agent.
    • Observe mode: Runs optimization same as training, but uses the GUI to show progress of evolution maybe every 10 generations if fitness improves
    • Battle Mode: Runs a game with one agent loaded from our training and the user playing with keys against that agent

Is there an infinite loop in breeding? Should we be eliminating worst from EACH species? if noone improves for 15 generations, we essentially die

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Training neural nets to play capture the flag Pacman variant through NeuroEvolution of Augmenting Topologies

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  • Python 62.1%
  • Cython 31.8%
  • HTML 6.1%