A learning approach to swarm-based path detection and tracking

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

Swarm intelligence for scheduling: a review

Swarm Intelligence generally refers to a problem-solving ability that emerges from the interaction of simple information-processing units. The concept of Swarm suggests multiplicity, distribution, stochasticity, randomness, and messiness. The concept of Intelligence suggests that problem-solving approach is successful considering learning, creativity, cognition capabilities. This paper introduces some of the theoretical foundations, the biological motivation and fundamental aspects of swarm intelligence based optimization techniques such Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Artificial Bees Colony (ABC) algorithms for scheduling optimization.

Structural Connectivity Of The Default Mode Network And Cognition In Alzheimer׳s Disease.

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.

A hybrid Particle Swarm Optimization - Simplex algorithm (PSOS) for structural damage identification

This study proposes a new PSOS-model based damage identification procedure using frequency domain data. The formulation of the objective function for the minimization problem is based on the Frequency Response Functions (FRFs) of the system. A novel strategy for the control of the Particle Swarm Optimization (PSO) parameters based on the Nelder-Mead algorithm (Simplex method) is presented; consequently, the convergence of the PSOS becomes independent of the heuristic constants and its stability and confidence are enhanced. The formulated hybrid method performs better in different benchmark functions than the Simulated Annealing (SA) and the basic PSO (PSO(b)). Two damage identification problems, taking into consideration the effects of noisy and incomplete data, were studied: first, a 10-bar truss and second, a cracked free-free beam, both modeled with finite elements. In these cases, the damage location and extent were successfully determined. Finally, a non-linear oscillator (Duffing oscillator) was identified by PSOS providing good results. (C) 2009 Elsevier Ltd. All rights reserved

Multiobjective Particle Swarm Approach for the Design of a Brushless DC Wheel Motor

The roots of swarm intelligence are deeply embedded in the biological study of self-organized behaviors in social insects. Particle swarm optimization (PSO) is one of the modern metaheuristics of swarm intelligence, which can be effectively used to solve nonlinear and non-continuous optimization problems. The basic principle of PSO algorithm is formed on the assumption that potential solutions (particles) will be flown through hyperspace with acceleration towards more optimum solutions. Each particle adjusts its flying according to the flying experiences of both itself and its companions using equations of position and velocity. During the process, the coordinates in hyperspace associated with its previous best fitness solution and the overall best value attained so far by other particles within the group are kept track and recorded in the memory. In recent years, PSO approaches have been successfully implemented to different problem domains with multiple objectives. In this paper, a multiobjective PSO approach, based on concepts of Pareto optimality, dominance, archiving external with elite particles and truncated Cauchy distribution, is proposed and applied in the design with the constraints presence of a brushless DC (Direct Current) wheel motor. Promising results in terms of convergence and spacing performance metrics indicate that the proposed multiobjective PSO scheme is capable of producing good solutions.

Swarm Intelligence applied in synthesis of hunting strategies in a three-dimensional environment

Systems of distributed artificial intelligence can be powerful tools in a wide variety of practical applications. Its most surprising characteristic, the emergent behavior, is also the most answerable for the difficulty in. projecting these systems. This work proposes a tool capable to beget individual strategies for the elements of a multi-agent system and thereof providing to the group means on obtaining wanted results, working in a coordinated and cooperative manner as well. As an application example, a problem was taken as a basis where a predators` group must catch a prey in a three-dimensional continuous ambient. A synthesis of system strategies was implemented of which internal mechanism involves the integration between simulators by Particle Swarm Optimization algorithm (PSO), a Swarm Intelligence technique. The system had been tested in several simulation settings and it was capable to synthesize automatically successful hunting strategies, substantiating that the developed tool can provide, as long as it works with well-elaborated patterns, satisfactory solutions for problems of complex nature, of difficult resolution starting from analytical approaches. (c) 2007 Elsevier Ltd. All rights reserved.

On Building a Memory Evolutive System for Application to Learning and Cognition Modeling

We address here aspects of the implementation of a memory evolutive system (MES), based on the model proposed by A. Ehresmann and J. Vanbremeersch (2007), by means of a simulated network of spiking neurons with time dependent plasticity. We point out the advantages and challenges of applying category theory for the representation of cognition, by using the MES architecture. Then we discuss the issues concerning the minimum requirements that an artificial neural network (ANN) should fulfill in order that it would be capable of expressing the categories and mappings between them, underlying the MES. We conclude that a pulsed ANN based on Izhikevich`s formal neuron with STDP (spike time-dependent plasticity) has sufficient dynamical properties to achieve these requirements, provided it can cope with the topological requirements. Finally, we present some perspectives of future research concerning the proposed ANN topology.

Studies of Cognition and Emotion in Organisations: Attribution, Affective Events, Emotional Intelligence and Perception of Emotion

This article details the author’s attempts to improve understanding of organisational behaviour through investigation of the cognitive and affective processes that underlie attitudes and behaviour. To this end, the paper describes the author’s earlier work on the attribution theory of leadership and, more recently, in three areas of emotion research: affective events theory, emotional intelligence, and the effect of supervisors’ facial expression on employees’ perceptions of leader-member exchange quality. The paper summarises the author’s research on these topics, shows how they have contributed to furthering our understanding of organisational behaviour, suggests where research in these areas are going, and draws some conclusions for management practice.

Psychophysiological phenotypes of cognition: The P3 and SW components

As part of a large ongoing project, the Memory, Attention and Problem Solving (MAPS) study, we investigated whether genetic variability explains some of the variance in psychophysiological correlates of brain function, namely, the P3 and SW components of event-related potentials (ERPs). These ERP measures are minute time recordings of brain processes and, because they reflect fundamental cognitive processing, provide a unique window on the millisecondto- millisecond transactions that occur at the cognitive level and taking place in the human brain. The extent to which the variance in P3 and SW components is influenced by genetic factors was examined in 350 identical and nonidentical twin pairs aged 16 years. ERPs were recorded from 15 scalp electrodes during the performance of a visuospatial delayed response task that engages working memory. Multivariate genetic analyses using MX were used to estimate genetic and environmental influences on individual differences in brain functioning and to identify putative genetic factors common to the ERP measures and psychometric IQ. For each of the ERP measures, correlation among electrode sites was high, a spatial pattern was evident, and a large part of the genetic variation in the ERPs appeared to be mediated by a common genetic factor. Moderate within-pair concordance in MZ pairs was found for all ERP measures, with higher correlations found for P3 than SW, and the MZ twin pair correlations were approximately twice the DZ correlations, suggesting a genetic influence. Correlations between ERP measures and psychometric IQ were found and, although moderately low, were evident across electrode site. The analyses show that the ERP components, P3 and SW, are promising phenotypes of the neuroelectrical activity of the brain and have the potential to be used in linkage and association analysis in the search for QTLs influencing cognitive function.

Nestmate recognition in a Neotropical swarm-founding wasp: no effect of seasonality on tolerance of alien conspecifics

Previous study revealed that the swarm-founding wasp Polybia paulista is accurately able to distinguish nestmates from non-nestmates in the summer. However, the risk of accepting alien intruders is considered to be low in winter colonies, and additionally brood production is limited in 30-40% of colonies during the winter in this species. Thus, it is expected that colonies might lower their acceptance threshold and accept some conspecific wasps from alien colonies in winter. We conducted field experiments to examine tolerance of conspecific (nestmate and non-nestmate) females in winter. In contrast to our prediction, our colonies did not accept any individuals from alien colonies. We suggest that P. paulista exhibits the colony-specific acceptance threshold in winter, and colonies that produced brood in their nests may have raised the acceptance threshold even if the risk of accepting alien intruders is low in winter.

Worker demography in a large-colony, swarm-founding wasp

Neotropical swarm-founding wasps build nests enclosed in a covering envelope, which makes it difficult to count individual births and deaths. Thus, knowledge of worker demography is very limited for swarm-founding species compared with that for independent-founding species. In this study, we explored the worker demography of the swarm-founding wasp Polybia paulista, the colony size of which usually exceeds several thousand adults. We considered each wasp colony as an open-population and estimated the survival probability, recruitment rate, and population size of workers using the developments of the Cormack-Jolly-Seber model. We found that capture probability varied considerably among the workers, probably due to age polyethism and/or task specialization. The daily survival rate of workers was high (around 0.97) throughout the season and was not related to the phase of colony development. On the other hand, the recruitment rate ranged from 0 to 0.37, suggesting that worker production was substantially less important than worker survival in determining worker population fluctuations. When we compared survival rates among worker groups of one colony, the mean daily survival rate was lower for founding workers than for progeny workers and tended to be higher in progeny workers that emerged in winter. These differences in survivorship patterns among worker cohorts would be related to worker foraging activity and/or level of parasitism.

Nest site selection by a neotropical swarm-founding wasp: seasonal alternation of nest orientation

Nest orientation in social insects has been intensively studied in warmer and cooler climates, particularly in the northern hemisphere. Previous studies have consistently shown that species subjected to these climatic conditions prefer to select mostly southern locations where the nests can gain direct sunlight. However, very little is known on nest orientation in tropical and subtropical social insects. We studied nest orientations initiated by swarms throughout a year in a Brazilian swarm-founding wasp, Polybia paulista von Ihering (Hymenoptera: Polistinae). Swarms selected various orientations as nest sites, but there was a particular trend in that swarms in the winter period (May-August) preferred to build northward-facing nests. This preference is opposite from that of social wasps observed in the northern hemisphere. Colonies of this species can potentially last for many years with continuous nesting, but nesting activities of colonies during the winter are severely limited due to cool temperature and a shortened day length. Northward-facing nests are warmer through the gain of direct solar heat during the winter period; consequently, choosing northward-facing sites may be advantageous for swarms in terms of a shortened brood development and shortened time needed to increase metabolic rates during warm-up for flight.

Homocysteine, Alzheimer genes and proteins, and measures of cognition and depression in older men

The epsilon4 allele of apolipoprotem E (APOE), and the plasma levels of APOE, amyloid beta-protein precursor, arnyloid beta1-40 (Abeta40) and homocysteine, (Hcy) have all been correlated with the presence of dementia. Mutations in the methylnetetrahydrofolate reductase enzyme (MTHFR) have been associated with elevated levels of Hcy. This study explored the association of these factors with cognition and depression in community dwelling older men. Two hundred and ninety-nine men, mean age 78.9 years (SD 2.8), were studied in this cross-sectional survey. Mean plasma Hcy was 13.5 (SD 5.3) mumol/L. The MTHFR genotype had no obvious impact on Hey levels. Ln Hcy and Ln Abeta40 were both inversely correlated with calculated glomerular filtration rate (cGFR), r = -0.41 (p < 0.001) and r = -0.28 (p < 0.001), respectively. There was a positive correlation between Ln Hey and Ln Abeta40, r = 0.19 (p < 0.001), which remained significant after adjusting for cGFR, with a doubling of Hcy associated with a 24% increase of Abeta40. The e4 allele was associated with increased depressive symptoms as measured by the Geriatric Depression Scale-15, Odds ratio (OR) = 2.59 (95% CI 1.06-6.34) and poorer performance on the Clock Drawing Test, OR = 2.32 (95% CI: 1.25-4.29). There was a positive association between Abeta40 and Hcy, even after adjustment for cGFR in this sample of well, community dwelling older men. This association may help elucidate the link between elevated levels of Hey and Alzheimer's disease.