Solving linear systems with a large number of variables is at the core of many scienti c problems. Parallel processing techniques for solving such systems have received much attent...
Arun Nagari, Itamar Elhanany, Ben Thompson, Fangxi...
In the past, Markov Decision Processes (MDPs) have become a standard for solving problems of sequential decision under uncertainty. The usual request in this framework is the compu...
Structured Hidden Markov Model (S-HMM) is a variant of Hierarchical Hidden Markov Model that shows interesting capabilities of extracting knowledge from symbolic sequences. In fact...
Whenever independent, non-cooperative actors jointly have to solve a complex task, they need to coordinate their efforts. Typical examples of such task coordination problems are s...
Hierarchical state machines are finite state machines whose states themselves can be other machines. In spite of their popularity in many modeling tools for software design, very l...