Fitness Landscape

Fitness landscapes visualize the relationship between a system's configuration (e.g., gene sequence, algorithm parameters) and its performance (fitness). Research currently focuses on characterizing these landscapes for diverse systems, including protein design, machine learning hyperparameter optimization, and evolutionary algorithms, often employing models like NK landscapes and local optima networks for analysis. Understanding fitness landscape structure is crucial for improving optimization algorithms, designing more robust systems, and accelerating progress in fields ranging from biotechnology to artificial intelligence. This involves developing new analytical techniques and applying them to increasingly complex systems to better understand the challenges and opportunities presented by different landscape topographies.