Towards Metrics and Visualizations Sensitive to Coevolutionary Failures

Ari Bader-Natal and Jordan B. Pollack

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-ofgeneration data, we demonstrate one such techique — 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.

This page is copyrighted by AAAI. All rights reserved. Your use of this site constitutes acceptance of all of AAAI's terms and conditions and privacy policy.