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...
Decentralized reinforcement learning (DRL) has been applied to a number of distributed applications. However, one of the main challenges faced by DRL is its convergence. Previous ...
Chongjie Zhang, Victor R. Lesser, Sherief Abdallah
—The complexity of distributed computing systems and their increasing interaction with the physical world impose challenging requirements in terms of adaptation, robustness, and ...
Increasingly, applications need to be able to self-reconfigure in response to changing requirements and environmental conditions. Autonomic computing has been proposed as a means...
Andres J. Ramirez, David B. Knoester, Betty H. C. ...
Abstract. This paper presents a model of the co-evolution of transmissible disease and a population of non-randomly mixed susceptible agents. The presence of the disease elements i...