Approaches to computational intelligence, including neural networks, fuzzy systems and evolutionary computation, are converging to a common frontier --autonomous mental development (AMD). This article explains what AMD is and why computational intelligence can fully expand its power at this frontier. As an example, this paper discusses a theory, an architecture, and some experimental results of...

This paper is concerned with generalized second-order contingent epiderivatives of frontier and solution maps in parametric vector optimization problems. Under some mild conditions, we obtain some formulas for computing generalized second-order contingent epiderivatives of frontier and solution maps, respectively. We also give some examples to illustrate the corresponding results.

Exploration and mapping are fundamental prerequisites for autonomous robots operating in initially unknown environments. In this paper, we evaluate simple yet efficient frontier-based exploration strategies. Furthermore, we discuss improvements to the classic frontier-based exploration strategy by Yamauchi et al. that further shorten the resulting exploration paths and present results from a co...

An effective approach to decision support in multicriteria decision making (MCDM) problems characterized by three to eight decision criteria is described. The approach is based on approximating the feasible set in the criterion space (or a broader criterion set, which has the same Pareto frontier) and visualization of the Pareto frontier by interactive displaying bi-criterion slices of this set...

Astrosociology is a relatively new multidisciplinary field that scientifically investigates astrosocial phenomena (i.e., social, cultural, and behavioral patterns related to space exploration and related issues). The “astrosociological frontier” represents an analogous framework to that of space as the “final frontier,” as both territories are quite empty of human activity and ripe for explorat...

Mean-variance (MV) analysis is often sensitive to model mis-specification or uncertainty, meaning that the MV efficient portfolios constructed with an estimate of the model parameters (i.e., the expected return vector and covariance of asset returns) can give very poor performance for another set of parameters that is similar and statistically hard to distinguish from the one used in the analys...