Abstract. We study optimal control in large stochastic multi-agent systems in continuous space and time. We consider multi-agent systems where agents have independent dynamics with...
We consider regularized stochastic learning and online optimization problems, where the objective function is the sum of two convex terms: one is the loss function of the learning...
The sensor scheduling problem can be formulated as a controlled hidden Markov model and this paper solves the problem when the state, observation and action spaces are continuous....
Sumeetpal S. Singh, Nikolaos Kantas, Ba-Ngu Vo, Ar...
Response Surface Methodology (RSM) is a metamodelbased optimization method. Its strategy is to explore small subregions of the parameter space in succession instead of attempting ...
We have presented an optimal on-chip buffer allocation and buffer insertion methodology which uses stochastic models of the architecture. This methodology uses finite buffer s...
Sankalp Kallakuri, Nattawut Thepayasuwan, Alex Dob...