Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

Lattice structure on some fuzzy algebraic systems

In this paper, we study the lattice structure of some fuzzy algebraic systems such as (G-)fuzzy groups, some fuzzy ordered algebras and fuzzy hyperstructures. We prove that under suitable conditions, these structures form a distributive or modular lattice. This research partially is supported by the “ Fuzzy Systems and its Applications Center of Excelence, Shahid Bahonar University of Kerman, Iran”.     

Sensor Selection in Arbitrary Dimensions

We address the sensor selection problem which arises in tracking and localization applications. In sensor selection, the goal is to select a small number of sensors whose measurements provide a good estimate of a target's state (such as location). We focus on the bounded uncertainty sensing model where the target is a point in the d -dimensional Euclidean space. Each sensor measurement corresponds to a convex polyhedral subset of the space. The measurements are merged by intersecting corresponding sets. We show that, on the plane, four sensors are sufficient (and sometimes necessary) to obtain an estimate whose area is at most twice the area of the best possible estimate (obtained by intersecting all measurements). We also extend this result to arbitrary dimensions and show that a constant number of sensors suffice for a constant factor approximation in arbitrary dimensions. Both constants depend on the dimensionality of the space but are independent of the total number of sensors in the network.     

Toward Human Level Machine Intelligence - Is It Achievable? The Need for a Paradigm Shift

Officially, AI was born in 1956. Since then, very impressive progress has been made in many areas - but not in the realm of human level machine intelligence. During much of its early history, AI "was rife "with exaggerated expectations. A headline in an article published in the late forties of last century was headlined, "Electric brain capable of translating foreign languages is being built". Today, more than half a century later, we do have translation software, but nothing that can approach the quality of human translation. Clearly, achievement of human level machine intelligence is a challenge that is hard to meet. A prerequisite to achievement of human level machine intelligence is mechanization of these capabilities and, in particular, mechanization of natural language understanding. To make significant progress toward achievement of human level machine intelligence, a paradigm shift is needed. More specifically, what is needed is an addition to the armamentarium of AI of two methodologies: (a) a nontraditional methodology of computing with words (CW) or more generally, NL-Computation; and (b) a countertraditional methodology "which involves a progression from computing with numbers to computing with words. The centerpiece of these methodologies is the concept of precisiation of meaning. Addition of these methodologies to AI would be an important step toward the achievement of human level machine intelligence and its applications in decision-making, pattern recognition, analysis of evidence, diagnosis, and assessment of causality. Such applications have a position of centrality in our infocentric society.     

QoS assessment of 3G video-phone calls by tracing watermarking exploiting the new colour space `YST?

Tracing watermarking has been recently proposed as a technique to provide a blind measure of the quality of service of the communication link, focusing on multimedia communication scenarios. 3G communication scenarios, where each customer transmits both voice and MPEG-4 video sequences in real time, have been considered. Typical video-phone call consists of close shots of speakers, framing their face in the foreground. For such particular application, a novel colour space (YST) is adopted to minimise the perceptual distortions on face coding introduced by watermarking. In the YST space, the luminance component (Y) is the same as in conventional YUV space, whereas the vectors S and T lie within the chrominance (UV) plane. The S (skin) component is a linear combination of U and V obtained as the 'average' chrominance estimated from an assorted set human faces to achieve a reasonable generalisation. The third component, T, is defined as orthogonal to the YS plane. The results show the benefits obtained in digital watermarking by the new representation against the conventional approach. In fact, the sensitivity of the YST representation outperforms the conventional one in terms of objective (mean square error, peak signal-to-noise ratio) and subjective (video-quality metrics) indicators.     

Entrainment and musicality in the human system interface

What constitutes our human capacity to engage and be in the same frame of mind as another human? How do we come to share a sense of what ‘looks good’ and what ‘makes sense’? How do we handle differences and come to coexist with them? How do we come to feel that we understand what someone else is experiencing? How are we able to walk in silence with someone familiar and be sharing a peaceful space? All of these aspects are part of human ‘interaction’. In designing interactive technologies designers have endeavoured to explicate, analyse and simulate, our capacity for social adaptation. Their motivations are mixed and include the desires to improve efficiency, improve consumption, to connect people, to make it easier for people to work together, to improve education and learning. In these endeavours to explicate, analyse and simulate, there is a fundamental human capacity that is beyond technology and that facilitates these aspects of being, feeling and thinking with others. That capacity, we suggest, is human entrainment. This is our ability to coordinate the timing of our behaviours and rhythmically synchronise our attentional resources. Expressed within the movements of our bodies and voices, it has a quality that is akin to music. In this paper, disparate domains of research such as pragmatics, social psychology, behaviourism, cognitive science, computational linguistics, gesture, are brought together, and considered in light of the developments in interactive technology, in order to shape a conceptual framework for understanding entrainment in everyday human interaction.     

Some Problems of Robust Control of a Stochastic Object

Studies are made of a problem of constructing a robust system according to an averaged performance criterion of a stochastic control system. Cases of the parametric and the structural uncertainty are considered. The relation of the notion of the stochastic robustness to the classical definition of deterministic systems is shown. A comparative analysis of the suggested method of developing a robust system and some other approaches is carried out.