The “Bee Simulation” (or Adaptive Pathfinding in a Dynamic Energy Ecosystem) is an interactive digital environment where autonomous agents, called collectors, navigate a grid to interact with resource nodes. Nodes hold energy that the collectors seek to gather, following programmed pathfinding logic that prioritizes resource availability and proximity. Each node, when visited by a collector, depletes its energy and slowly recharges over time. When nodes become too depleted, they temporarily turn inactive, forcing collectors to adapt their strategies. The simulation is visually dynamic, underscored by a soothing pastel rainbow gradient background that shifts hues gradually. Collectors move with smooth animations, including bobbing motions, and display intelligent behaviors as they seek the most optimal nodes. The user can interact with the simulation by adding or removing nodes in real time, allowing for exploration of how changes in the system affect the balance of energy flow. Together, these elements create a dynamic, constantly evolving ecosystem that demonstrates the interplay between resource management and pathfinding.
The main goal of the project was to observe pathfinding behaviors in an engaging way. I wanted to create a system where agents would navigate a dynamic environment, responding to changes in real time as they moved between resources. The ecosystem framework provided an ideal setting for this, as the interaction between collectors and nodes created a clear structure for movement and decision-making. I wanted the system to feel cohesive and visually interesting, with elements like the gradient background and bobbing animations, and adding features like the real-time node placement to make the simulation more interactive and highlight how small changes could influence the collectors’ paths. Ultimately, the motivation came from a desire to see how simple rules could lead to behaviors that felt purposeful and adaptive. Observing how collectors responded to active or inactive nodes, prioritized certain paths, and balanced resource availability gave me a deeper appreciation for how movement systems can evolve in an ecosystem.
- The process started with a basic setup that included the background grid, three nodes, and a very simple movement mechanic for the collectors. From there, I sought feedback to refine my approach and decided on a more complex system to make the collectors’ behaviors more dynamic and interesting.
- I mapped out my ideas in a mix of pseudocode and written notes to clarify the mechanics. This helped me figure out how the collectors would prioritize nodes, how nodes would recharge over time, and how user interactions like adding or removing nodes would affect the simulation. These early drafts served as a guide, but much of the development involved working directly in code and refining as I went.
- I worked on the collectors, programming their movement and pathfinding logic. Initially, they moved in straight, stuttered motions between nodes. I made sure to focus on introducing a smooth wandering and bobbing mechanic to make the collectors feel more life-like. I also incorporated randomness into elements like node placement and collector target selection to keep each reload unique.
- After that, I focused on the nodes, ensuring they could handle energy depletion and recharge dynamics while switching between active and inactive states. This part required careful balancing to ensure that the ecosystem stayed functional over time. I kept going back and forth with the ratios between nodes and collectors, trying to find the right balance that would prevent the system from dying, but preventing each node from reaching a permanent ‘full status’.
- As a final failsafe for system balancing, I added the ability to add nodes by clicking and remove nodes by holding the space bar and clicking. This gives users more control over the ecosystem in real time, allowing them to shape its behavior dynamically. I implemented collision detection logic to ensure nodes cannot be placed too close to one another. This keeps the layout visually clear and prevents functional overlap.
- The visuals and music came last, tying everything together. I added in a shifting pastel gradient background to make the simulation feel soothing and calm. To add to this, I incorporated ambient background music to enhance the overall atmosphere of the simulation. Users can now control the audio with play, pause, and restart options, allowing for a more customizable experience.
- Of course, the development didn’t happen this linearly — I often jumped between sections and revisited parts that needed improvement. Overall, the development was a very iterative process, with frequent testing and adjustments to ensure the mechanics worked smoothly and the system felt balanced.
Since this semester has been my first true introduction to coding, this project has been a significant milestone and a great learning experience for me. Debugging and refining the system taught me how interconnected mechanics can be—fixing one issue often created new challenges elsewhere. This back-and-forth process deepened my understanding of how to balance complexity and clarity in a project, which has been both rewarding and humbling. This project reflects my growing interest in using code to build systems that feel alive and interactive. Working on this has been both challenging and fun, and it’s an experience I’m proud to have completed. I’m excited to take what I’ve learned here into more complex systems and explore how these skills can evolve in game design.
