A major challenge for traditional approaches to multiagent learning is to train teams that easily scale to include additional agents. The problem is that such approaches typically...
David B. D'Ambrosio, Joel Lehman, Sebastian Risi, ...
The development of the XCS Learning Classifier System [26] has produced a stable implementation, able to consistently identify the accurate and optimally general population of cla...
A vital task facing government agencies and commercial organizations that report data is to represent the data in a meaningful way and simultaneously to protect the confidentialit...
Fred Glover, Lawrence H. Cox, Rahul Patil, James P...
In this paper, we demonstrate the use of learning with non-uniform error-cost as a novel technique to design a multiclass cost-sensitive classifier. We investigate two important ...
In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combine...