My team's random walk though the space of ideas, eventually diffusing until nothing of them remained.

Feedback is a simple process that can create complicated results. Applying it to a stochastic process seemed a natural exploration, and this hackathon was the perfect excuse to spend a weekend doing it.

How it was done

Much python graphing. I learned a lot about matplotlib formatting.

Next steps

The methods for feeding back generated surprisingly predictable results. In future, it would be nice to explore feedback in more interesting systems, as I have explored the space of random walks quite thoroughly.

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