New Publication: "Towards Metrics and Visualizations Sensitive to Coevolutionary Failures"

The task of monitoring success and failure in coevolution is inherently difficult, as domains need not have any external metric to measure performance. Past metrics and visualizations for coevolution have been limited to identification and measurement of success but not failure. We suggest circumventing this limitation by switching from "best-of-generation"-based techniques to "all-of-generation"-based techniques. Using "all-of-generation" data, we demonstrate one such technique - a population-differential technique - that allows us to profile and distinguish an assortment of coevolutionary successes and failures, including arms-race dynamics, disengagement, cycling, forgetting, and relativism.