Problem Statement
To study the emergent behavior of simple cellular automata in complex social environments, using ant colonies as a model. Ant colonies can be modeled as a world where each individual ant moves between discrete states based only on its internal state and its perception of the local region. The ant colonies attain their goal of foraging for food through stigmergy which is a form of indirect communication. Individual ants modify their local environment by leaving a pheromone trail as a beacon for other ants who can then react to it.
Thus, the environment effectively stores the past collective knowledge of the entire ant colony regarding the status of the current goal. This provides the means by which simple creatures like ants can perform complex tasks. This project will specifically focus on the task of efficient foraging of food as a means for discovering the shortest path between two points; i.e. the ant hill to the food source.
Proposed Quantitative and Qualitative Questions
- How does the number of ants in the colony affect the convergence to the shortest path solution and what is numerical relationship between the two?
- What value of the explore rate yields the fastest convergence to a shortest path solution?
- How optimal are the paths discovered by the ant colony compared to the actual shortest path?