We offer a new formal criterion for agent-centric learning in multi-agent systems, that is, learning that maximizes one’s rewards in the presence of other agents who might also...
This paper describes a new approach to automatically learning linguistic knowledge for spelling correction. A major feature of this approach is the fact that the acquired knowledg...
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
TCP throughput prediction is an important capability in wide area overlay and multi-homed networks where multiple paths may exist between data sources and receivers. In this paper...
Mariyam Mirza, Joel Sommers, Paul Barford, Xiaojin...
This paper investigates a learning control using iterative error compensation for uncertain systems to enhance the precision of high speed, computer controlled machining process. ...