It feels great to be getting some code committed to our capstone project! I got into one of my top choices, the A-Life challenge. We’re taking inspiration from the deep history of artificial life games to create a simulator that supports environmental features, organism interactions, and simple genetics.

One thing we were all excited about was the possibility of having an environment that supports both different terrain types and biological domains. This should allow us to create randomized biomes (rocky areas, watery areas, grasslands) and populate our world with plants and animals. We’re still working on the details, and trying to design a framework that’s flexible enough to support both realistic and reach goals.

Right now we’re designing a simple genetics system based on a 32-bit binary integer. Different traits will be evaluated depending on the overall properties of different bits. It acts like a simple genetic sequence, but feels appropriate for digital creatures. This means users can tweak a genome, but the results might not immediately be obvious. It also allows for tradeoffs; for example, different traits might depend on the same gene having different values. So an organism might not be able to achieve maximum speed and maximum endurance, for example.

We’re also fortunate to have a teammate with front-end and design skills, so we can make a visual representation that reflects the lifecycles and interactions. We’re drawing visual style inspiration from some genre classics like the Game of Life and SimPark, going for some lo-fi charm. They are committing some code later today and I’m looking forward to a first look at the prototype interface. We’re also discussing backend details (how the clock cycle works, parallelism options) and coming up with some good ideas on that front. So far I’m glad we chose Python, as it has some excellent options for extending into both parallel programming and clean user interface. Excited to see where we are at this point next week!