MO-MFCGA: Multiobjective multifactorial cellular genetic algorithm for evolutionary multitasking

Multiobjetive optimization has gained a considerable momentum in the evolutionary computation scientific community. Methods coming from evolutionary computation have shown a remarkable performance for solving this kind of optimization problems thanks to their implicit parallelism and the simultaneous convergence towards the Pareto front. In any case, the resolution of multiobjective optimization problems (MOPs) from the perspective of multitasking optimization remains almost unexplored. Multitasking is an incipient research stream which explores how multiple optimization problems can be simultaneously addressed by performing a single search process. The main motivation behind this solving paradigm is to exploit the synergies between the different problems (or tasks) being optimized. Going deeper, we resort in this paper to the also recent paradigm Evolutionary Multitasking (EM). We introduce the adaptation of the recently proposed Multifactorial Cellular Genetic Algorithm (MFCGA) for solving MOPs, giving rise to the Multiobjective MFCGA (MO-MFCGA). An extensive performance analysis is conducted using the Multiobjective Multifactorial Evolutionary Algorithm as comparison baseline. The experimentation is conducted over 10 multitasking setups, using the Multiobjective Euclidean Traveling Salesman Problem as benchmarking problem. We also perform a deep analysis on the genetic transferability among the problem instances employed, using the synergies among tasks aroused along the MO-MFCGA search procedure

Bestial boredom: a biological perspective on animal boredom and suggestions for its scientific investigation

Boredom is likely to have adaptive value in motivating exploration and learning, and many animals may possess the basic neurological mechanisms to support it. Chronic inescapable boredom can be extremely aversive, and understimulation can harm neural, cognitive and behavioural flexibility. Wild and domesticated animals are at particular risk in captivity, which is often spatially and temporally monotonous. Yet biological research into boredom has barely begun, despite having important implications for animal welfare, the evolution of motivation and cognition, and for human dysfunction at individual and societal levels. Here I aim to facilitate hypotheses about how monotony affects behaviour and physiology, so that boredom can be objectively studied by ethologists and other scientists. I cover valence (pleasantness) and arousal (wakefulness) qualities of boredom, because both can be measured, and I suggest boredom includes suboptimal arousal and aversion to monotony. Because the suboptimal arousal during boredom is aversive, individuals will resist low arousal. Thus, behavioural indicators of boredom will, seemingly paradoxically, include signs of increasing drowsiness, alongside bouts of restlessness, avoidance and sensation-seeking behaviour. Valence and arousal are not, however, sufficient to fully describe boredom. For example, human boredom is further characterized by a perception that time ‘drags’, and this effect of monotony on time perception can too be behaviourally assayed in animals. Sleep disruption and some abnormal behaviour may also be caused by boredom. Ethological research into this emotional phenomenon will deepen understanding of its causes, development, function and evolution, and will enable evidence-based interventions to mitigate human and animal boredom

Neural markers of a greater female responsiveness to social stimuli

Abstract Background There is fMRI evidence that women are neurally predisposed to process infant laughter and crying. Other findings show that women might be more empathic and sensitive than men to emotional facial expressions. However, no gender difference in the brain responses to persons and unanimated scenes has hitherto been demonstrated. Results Twenty-four men and women viewed 220 images portraying persons or landscapes and ERPs were recorded from 128 sites. In women, but not in men, the N2 component (210–270) was much larger to persons than to scenes. swLORETA showed significant bilateral activation of FG (BA19/37) in both genders when viewing persons as opposed to scenes. Only women showed a source of activity in the STG and in the right MOG (extra-striate body area, EBA), and only men in the left parahippocampal area (PPA). Conclusion A significant gender difference was found in activation of the left and right STG (BA22) and the cingulate cortex for the subtractive condition women minus men, thus indicating that women might have a greater preference or interest for social stimuli (faces and persons).</p

Language in Language Evolution Research: In Defense of a Pluralistic View

Many controversies in language evolution research derive from the fact that language is itself a natural language word, which makes the underlying concept fuzzy and cumbersome, and a common perception is that progress in language evolution research is hindered because researchers do not ‘talk about the same thing’. In this article, we claim that agreement on a single, top-down definition of language is not a sine qua non for good and productive research in the field of language evolution. First, we use the example of the notion FLN (‘faculty of language in the narrow sense’) to demonstrate how the specific wording of an important top-down definition of (the faculty of) language can—surprisingly—be inconsequential to actual research practice. We then review four approaches to language evolution that we estimate to be particularly influential in the last decade. We show how their breadth precludes a single common conceptualization of language but instead leads to a family resemblance pattern, which underwrites fruitful communication between these approaches, leading to cross-fertilisation and synergies

The dimensions of personality in humans and other animals: A comparative and evolutionary perspective

This paper considers the structure and proximate mechanisms of personality in humans and other animals. Significant similarities were found between personality structures and mechanisms across species in at least two broad traits: Extraversion and Neuroticism. The factor space tapped by these personality dimensions is viewed as a general integrative framework for comparative and evolutionary studies of personality in humans and other animals. Most probably, the cross-species similarities between the most broad personality dimensions like Extraversion and Neuroticism as well as other Big Five factors reflect conservative evolution: constrains on evolution imposed by physiological, genetic and cognitive mechanisms. Lower-order factors, which are more species- and situation-specific, would be adaptive, reflecting correlated selection on and trade-offs between many traits

Evolutionary Computation 2020

Intelligent optimization is based on the mechanism of computational intelligence to refine a suitable feature model, design an effective optimization algorithm, and then to obtain an optimal or satisfactory solution to a complex problem. Intelligent algorithms are key tools to ensure global optimization quality, fast optimization efficiency and robust optimization performance. Intelligent optimization algorithms have been studied by many researchers, leading to improvements in the performance of algorithms such as the evolutionary algorithm, whale optimization algorithm, differential evolution algorithm, and particle swarm optimization. Studies in this arena have also resulted in breakthroughs in solving complex problems including the green shop scheduling problem, the severe nonlinear problem in one-dimensional geodesic electromagnetic inversion, error and bug finding problem in software, the 0-1 backpack problem, traveler problem, and logistics distribution center siting problem. The editors are confident that this book can open a new avenue for further improvement and discoveries in the area of intelligent algorithms. The book is a valuable resource for researchers interested in understanding the principles and design of intelligent algorithms

Neuro-Immune Abnormalities in Autism and Their Relationship with the Environment: A Variable Insult Model for Autism

Autism spectrum disorder (ASD) is a heterogeneous condition affecting an individual’s ability to communicate and socialize and often presents with repetitive movements or behaviors. It tends to be severe with less than 10% achieving independent living with a marked variation in the progression of the condition. To date, the literature supports a multifactorial model with the largest, most detailed twin study demonstrating strong environmental contribution to the development of the condition. Here, we present a brief review of the neurological, immunological, and autonomic abnormalities in ASD focusing on the causative roles of environmental agents and abnormal gut microbiota. We present a working hypothesis attempting to bring together the influence of environment on the abnormal neurological, immunological, and neuroimmunological functions and we explain in brief how such pathophysiology can lead to, and/or exacerbate ASD symptomatology. At present, there is a lack of consistent findings relating to the neurobiology of autism. Whilst we postulate such variable findings may reflect the marked heterogeneity in clinical presentation and as such the variable findings may be of pathophysiological relevance, more research into the neurobiology of autism is necessary before establishing a working hypothesis. Both the literature review and hypothesis presented here explore possible neurobiological explanations with an emphasis of environmental etiologies and are presented with this bias