As a developer, I was fascinated by the concept of swarm intelligence and its potential applications in optimization problems. I decided to dive deeper into the world of particle swarm optimization and started working on developing a visualization. Alongside visualizing, fundamentally understanding this complex algorithm. In our natural world we can see it perform with species such as bees or ants working as a community to solve problems. After hours of coding and testing, I finally had a working prototype that could find optimal solutions, in this case the minimum of a function. However, I wanted to take it a step further and visualize the behavior of the particles in the swarm. With the help of some advanced data visualization tools, such as Matplotlib, I was able to create captivating visualizations that showed the particles moving towards the optimal solution. Seeing the algorithm in action was a truly rewarding experience, and it gave me a deeper appreciation for the power of swarm intelligence.

Here is the recent gif generated by my code recently: This GIF demonstrates a uniformly distributed selection of agents placed onto a polynomial plot. Combining social and cognative weights to optimize as a swarm. Some particles get stuck in the middle torn between two minimums.

Many more stages of development is soon to come with stunning visuals in both two and three dimensions.

Thank you for your time and the read, Drew Sapato