Nature-Inspired Computing

Nature-Inspired Computing is a branch of computer science that develops algorithms and systems modeled after natural processes and behaviors found in the environment. It leverages principles such as evolution, swarm behavior, and neural activity to solve complex problems more efficiently. Examples include genetic algorithms, which mimic natural selection, and ant colony optimization, inspired by how ants find the shortest paths to food. This approach often leads to innovative solutions in optimization, machine learning, and problem-solving tasks, drawing strength from nature’s proven strategies for adaptation, cooperation, and resilience.