Abstract. We adopt the Markov chain framework to model bilateral negotiations among agents in dynamic environments and use Bayesian learning to enable them to learn an optimal stra...
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
Particle Swarm Optimization (PSO) is a population-based stochastic optimization technique, which can be used to find an optimal, or near optimal, solution to a numerical and quali...
Dynamic Power Management (DPM) is a design methodology aiming at reducing power consumption of electronic systems by performing selective shutdown of idle system resources. The eff...
— We consider systems of mobile robots that execute a transportation task and periodically recharge from a docking station. The location of the docking station has a considerable...