A central problem in multistrategy learning systems is the selection and sequencing of machine learning algorithms for particular situations. This is typically done by the system ...
Previous research in real-time concurrency control mainly focuses on the schedulability guarantee of hard real-time transactions and the reducing of the miss rate of soft real-tim...
Kam-yiu Lam, Tei-Wei Kuo, Ben Kao, Tony S. H. Lee,...
A significant body of work in multiagent systems over more than two decades has focused on multi-agent coordination (1). Many challenges in multi-agent coordination can be modeled ...
A parallel computing approach for large-scale SPICE-accurate circuit simulation is described that is based on a new preconditioned iterative solver. The preconditioner involves the...
Heidi Thornquist, Eric R. Keiter, Robert J. Hoekst...
Team strategy acquisition is one of the most important issues of multiagent systems, especially in an adversary environment. RoboCup has been providing such an environment for AI a...