We present a novel computational model aimed at exploring the concept of developmental exaptations, a previously hypothesized phenomenon wherein existing aspects of a developmental process are reused for a new, beneficial function. We leverage computational simulations to study this due to the challenges of observing developmental exaptations directly in nature. Employing a special fitness landscape, our model simulates the evolution of developmental strategies, allowing the study of how certain developmental instructions, which were initially evolved for a different function (or no function), can be repurposed to enhance fitness. The model utilizes indirect encoding to mimic biological processes, facilitating the evolution of exaptations. We demonstrate how crucial mutations contribute to achieving global fitness maxima, indicative of developmental exaptations for our special landscape. Our results not only provide computational evidence for the plausibility of developmental exaptations, but also open avenues for further research into detecting and understanding these phenomena in more complex and dynamic environments. This work establishes a new approach for modeling and analyzing developmental exaptations.

The study of evolutionary development (evo-devo) is frequently challenged by the scales of space and time complexity inherent to its study. This has led to the creation of abstract models to allow for the exploration of evo-devo in a manner that is both more computationally feasible and more general, without ties to the specific biological processes of a single organism. Our work expands upon these previous models by introducing an indirect encoding for developmental mechanisms, dynamic fitness landscapes, and a phenotypic structure that allows for the exploration of new interactions between the developmental and evolutionary processes. Introducing these changes allows us to conduct a more thorough study of factors impacting evo-devo. Our experimental results suggest a number of parallels to biological systems. These include representing the synergy of evolutionary and developmental processes, the evolution of adaptable features, and highly conserved regulatory genes. We also discuss the opportunities for exploration opened by this new model. These possibilities include the study of developmental exaptations and the robustness of developmental strategies.

Evolution and development are related processes although their relationship is still not well understood. Attempts to explore their relationship are challenged by scales of time and space, but also by the limitations of studies focused on specific constraints of model organisms. To help gain insight into these phenomena, we create an abstract, general model of a developmental process that guides an agent’s trajectory through a “tunably rugged” NK fitness landscape. The developmental process is represented by a genotype that is evolved and allows us to investigate periods of exploration and exploitation as they relate to periods of an agent’s lifetime and a given landscape’s difficulty. Results show that evolution selects for time-sensitive periods of exploration and exploitation, which vary with the difficulty of the landscapes being traversed. Furthermore, our analysis suggests that phenotypic diversity via random exploration present in both early and mid-life can aid the development of superior phenotypes.