The vestibular system helps maintain equilibrium and clear vision through reflexes, but it also contributes to spatial perception. In recent years, research in the vestibular field has expanded to higher-level processing involving the cortex. Vestibular contributions to spatial cognition have been difficult to study because the circuits involved are inherently multisensory. Computational method...

In this paper we present a multi-scale morphological method for use in texture classification. A connected operator similar to the morphological hat-transform is defined, and two scale-space representations are built. The most important features are extracted from the scale spaces by unsupervised cluster analysis, and the resulting pattern vectors provide the input of a decision tree classifier...

Introduction Modern decision theory is full of talk about subjective probabilities and utilities. While these concepts fill something like the functional roles traditionally filled by belief and desire in philosophical discourse, the relationship between the old and new realizers is usually left unclear. A central piece of this puzzle is the relationship between subjective probability and belie...

Satellite constellation design is one kind of typical Multiobjective Optimization Problem (MOP). In this paper, aim at feature of high-dimensional decision space, an model-based multiobjective Evolutionary Algorithm(EA) via Self Organization Feature Map(SOM) is put forward for reducing decision space dimension of satellite constellation design: internal topology of input training set in the pop...

Multi-modal multi-objective optimization problems (MMMOPs) have multiple subsets within the Pareto-optimal Set, each independently mapping to same Pareto-Front. Prevalent evolutionary algorithms are not purely designed search for solution subsets, whereas, MMMOPs demonstrate degraded performance in objective space. This motivates design of better addressing MMMOPs. The present work identifies c...

We propose a simple analytical model called M time-scale Markov Decision Process (MMDP) for hierarchically structured sequential decision making processes, where decisions in each level in the M -level hierarchy are made in M different time-scales. In this model, the state space and the action space of each level in the hierarchy are non-overlapping with those of the other levels, respectively,...