Fitness is a quantification of an individual’s evolutionary success. In biology, an individual’s fitness is generally measured as the number of offspring that individual has. Many artificial life platforms operate in the same manner, encoding rules that determine when individuals reproduce and then allowing evolution to take its course (some individuals will reproduce more, consequently there will be more of them; the composition of the population will just shift over time to be primarily composed of those individuals that reproduce the most). This approach is known as “implicit fitness”, and is used by systems such as Avida.
In contrast, other artificial life systems use “explicit fitness”. In this context, fitness is not a property to be measured, it is a property that is set. The system then replicates individuals in accordance with their set fitness. This approach is particularly common in evolutionary computation and other systems that use evolution as an optimization algorithm. For example, fitness may be assigned based on how well an organism is able to solve a specific problem.