In concurrent cooperative multiagent learning, each agent simultaneously learns to improve the overall performance of the team, with no direct control over the actions chosen by i...
We present a novel method for automatically acquiring strategies for the double auction by combining evolutionary optimization together with a principled game-theoretic analysis. ...
A major difficulty for anomaly detection lies in discovering boundaries between normal and anomalous behavior, due to the deficiency of abnormal samples in the training phase. In...
We propose using the so called Royal Road functions as test functions for cooperative co-evolutionary algorithms (CCEAs). The Royal Road functions were created in the early 90’s ...
We present an anytime algorithm for coordinating multiple autonomous searchers to find a potentially adversarial target on a graphical representation of a physical environment. Th...