biologically-inspired algorithms

Biologically-inspired algorithms are problem-solving methods modeled after natural processes and behaviors observed in living organisms. They mimic systems like evolution, natural selection, or the way ants find the shortest path to food. These algorithms analyze large amounts of data and adapt over time, "learning" optimal solutions much like nature optimizes survival strategies. They are used in fields such as optimization, machine learning, and robotics to solve complex problems efficiently, drawing inspiration from biological systems that have proven effective in nature over millions of years.