Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Real life optimization problems often require finding optimal solution to complex high dimensional, multimodal problems involving computationally very expensive fitness function e...
Intelligent Transportation Systems (ITS) are a hot topic in the communications society. Currently, research is primarily focusing on setting up Vehicular Ad Hoc Networks (VANETs) ...
Christoph Sommer, Armin Schmidt, Yi Chen, Reinhard...
The workloads in modern Chip-multiprocessors (CMP) are becoming increasingly diversified, creating different resource demands on hardware substrate. It is necessary to allocate h...
We consider several classical models in deterministic inventory theory: the single-item lot-sizing problem, the joint replenishment problem, and the multi-stage assembly problem. ...