-Intro- This project uses a machine learning program. Machine learning is when a program can learn all by itself without being programmed. This one is really basic, and it works via natural selection. -Object- The fish (blue triangles) have to get to the goal (green dot) in order to pass their genes on to the next generation. If none of the fish make it in on time, the generation resets to 1, the fish get starting stats, and they start all over again. -Genes- The 3 genes in this simulation are GOAL, SPEED, and STRAIGHT. The goal gene is how slow the fish move in the goal. If the gene value is high, it will stick to the goal. The speed gene controls how fast the fish goes. But if a fish goes too fast, it might go past the goal! The straight gene is how much the fish don't turn. The fish are spawned in pointing towards the goal, so naturally higher values are a good thing. -History- Hover over the top-left corner to find the history. Each generation, a gene sample is taken from a random fish. The gene sample numbers are (from left to right): 1: The generation. 2: The goal gene. 3: The speed gene. And 4: The straight gene.
Everything is by me.
