Abstract
Natural evolution keeps inventing new complex and intricate forms and behaviors. Digital evolution and genetic algorithms fail to create the same kind of complexity, not just because we still lack the computational resources to rival nature, but because (it has been argued) we have not understood in principle how to create open-ended evolving systems. Much effort has been made to define such open-endedness so as to create forms of increasing complexity indefinitely. Here, however, a simple evolving computational system that satisfies all such requirements is presented. Doing so reveals a shortcoming in the definitions for open-ended evolution. The goal to create models that rival biological complexity remains. This work suggests that our current definitions allow for even simple models to pass as open-ended, and that our definitions of complexity and diversity are more important for the quest of open-ended evolution than the fact that something runs indefinitely.
Highlights
Open-ended evolution has been identified as a key challenge in artificial life research [4]
Requirement 5 demands a minimal criterion for replication, which is implemented here by using a proportionally higher replication chance if sequences are longer and traverse a path that is less frequented by other organisms
What remains are the demands for increasing diversity or complexity, and that this increase should happen forever
Summary
Open-ended evolution has been identified as a key challenge in artificial life research [4]. It has been acknowledged that there is a difference between an open-ended system and a system that just has a long run time. Large or slow systems will eventually converge on a solution, but openended systems will not and instead keep evolving. A system that oscillates or that is in a dynamic equilibrium [21] would continuously evolve, but does not count as an open-ended evolving system. While we seem to know well what an open-ended system is not, we struggle to find a positive definition of open-endedness [6, 7, 12, 18, 24, 26].1. While we seem to know well what an open-ended system is not, we struggle to find a positive definition of open-endedness [6, 7, 12, 18, 24, 26].1 In addition, we keep finding evidence leading us to refine previous constraints or requirements [18, 24]
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