"This book is devoted to recent developments, reviews and tutorials of decision making or optimization under uncertainty. Different models ranging from stochastic to grey and their connection will be outlines with highlighting possible future works along with applications on real case problems."

We consider function approximation by fuzzy systems. Fuzzy systems are typically used for approximating deterministic functions, in which the stochastic uncertainty is ignored. We propose probabilistic fuzzy systems in which the probabilistic nature of uncertainty is taken into account....

"[This book] is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem...

First-order approximation methods are a standard technique for analyzing the local dynamics of dynamic stochastic general equilibrium (DSGE) models. Although for a wide class of DSGE models linear methods yield quite accurate solutions, some important economic issues such as portfolio choice and...