Abstract-- Local convergence is a limitation of many optimization approaches for multimodal functions. For hybrid model learning, this can mean a compromise in accuracy. We develop...
Distributed systems can often be modeled as a collection of distributed (system) variables whose values are constrained by a set of constraints. In distributed multi-agent systems...
Wiebe van der Hoek, Cees Witteveen, Michael Wooldr...
Due to the increasing abstraction gap between the initial system model and a final implementation, the verification of the respective models against each other is a formidable task...
We address in this paper a problem of autonomous agents performing in a common environment where each agent has its goal to achieve before a given deadline. Agents must be able to...
Dynamic optimization relies on phase detection for two important functions (1) To detect change in code working set and (2) To detect change in performance characteristics that ca...