The importance of the efforts towards integrating the symbolic and connectionist paradigms of artificial intelligence has been widely recognised. Integration may lead to more e...
Despite many efforts, the predominant practice of debugging a distributed system is still printf-based log mining, which is both tedious and error-prone. In this paper, we present...
In many of today's applications, access to storage constitutes the major cost of processing a user request. Data prefetching has been used to alleviate the storage access lat...
Multi-Agent Reinforcement Learning (MARL) algorithms suffer from slow convergence and even divergence, especially in large-scale systems. In this work, we develop a supervision fr...
Chongjie Zhang, Sherief Abdallah, Victor R. Lesser
We present a performance analysis of an agent-based middleware system we have developed based on "reAgents," remotely executing agents that enhance the performance of cl...