Ant-Based Machine Learning

Ant-Based Machine Learning is a method inspired by how real ants find the shortest paths to food. In this approach, artificial "ants" explore data to discover patterns and optimal solutions by leaving "pheromone" trails that represent promising paths. Over time, better solutions accumulate more pheromone, guiding future searches toward the best options. This technique is useful for solving complex problems like routing, scheduling, and optimization by mimicking the collective behavior of ant colonies, effectively leveraging distributed, adaptive, and nature-inspired strategies to improve machine learning tasks.