The MODES toolbox: Measurements of Open-ended Dynamics in Evolving Systems

Building more open-ended evolutionary systems can simultaneously advance our understanding of biology, artificial life, and evolutionary computation. In order to do so, however, we need a way to determine when we are moving closer to this goal. We propose a set of metrics that allow us to measure commonly-agreed-upon hallmarks of open-ended evolution in a system: change potential, novelty potential, complexity potential, and ecological potential. Our goal is to make these metrics easy to incorporate into a system, and comparable across systems so that we can make coherent progress as a field. To this end, we provide a C++ implementation of these metrics that should be easy to connect to existing artificial life systems. As the field reaches consensus about additional hallmarks of open-ended evolution, metrics corresponding to these additions can be added to this toolbox. For example, we hope to soon add a measurement of the potential for major transitions in individuality to occur. To confirm that our metrics accurately measure the hallmarks we are interested in, we test them on two very different experimental systems: NK Landscapes and the Avida Digital Evolution Platform. We find that our observed results are consistent with our prior knowledge about these systems, suggesting that our proposed metrics are effective and should generalize to other systems.