Nasonov pheromone of the honeybee.Apis mellifera L. (Hymenoptera,Apidae)

Electroantennogram (EAG) responses from worker honeybee antennae were obtained for each Nasonov component. Response amplitudes to 10 g of components correlated well with reported relative abilities to attract foragers in the field. EAG responses of worker, queen, and drone antennae to natural pheromone were consistently greater than to synthetic pheromone, a difference only partly explained by enzymic conversion of geraniol to (E)-citral during preparation of natural extracts.     

Tracking variable environments: There is more than one kind of memory

Three kinds of memory help herbivores track changes in the environment. The first is the collective memory of the species with genetic instructions that have been shaped by the environment through millennia. This includes skin and gut defense systems. Auditory and visual stimuli and sensations of pain impinge upon the skin defense system that evolved in response to predation. The taste of food and the sensations of nausea and satiety are an integral part of the gut defense system that evolved in response to toxins and nutrients in plants. The second kind of memory in social mammals is represented by the mother, a source of transgenerational knowledge, who increases efficiency and reduces risk of learning about foods and environments. The third kind of memory is acquired by individual experience. Postingestive feedback from nutrients and toxins enables individuals to experience the consequences of food ingestion and to adjust food preference and selection commensurate with a food's utility. The three memories interact, each linking the past to the present, and collectively shape the present and future of every individual. Thus, the dynamics of foraging involves appreciating the uniqueness of individuals and subgroups of animals, each with their own genetic and behavioral history, and recognizing that foraging behaviors may not be stable, optimal, or even predictable in the conventional sense.     

基于区域分工机制的异构群体机器人觅食任务数学分析

根据机器人的能力进行区域分工,以提高群体机器人系统的觅食效率。为了系统研究异构群体机器人执行觅食任务时的群体行为,以比率方程为基础,构建了觅食任务的数学模型。并利用该模型,定量分析了机器人的数量及性能对觅食任务完成时间的影响。通过对数学模型的分析得出:外部机器人数增加时,外部机器人之间的干涉作用将减少觅食任务完成时间的改进;随着内部机器人与食物相遇率的提高,觅食任务完成时间的改进不断降低。     

Domestic dogs (Canis familiaris) use human gestures but not nonhuman tokens to find hidden food.

The authors examined the ability of domestic dogs to use human body cues (gestures) and equivalent-sized nonhuman cues to find hidden food in an object choice paradigm. In Experiment 1 the authors addressed the importance of the human element of the cue, and the effects of size, topography, and familiarity on dogs' success in using cues. Experiment 2 further explored the role of the human as cue-giver, and the impact of a change in the experimenter's attentional state during cue presentation. This included a systematic test of the role inanimate tokens play as cues apart from human placement. Our results indicate that dogs are more sensitive to human cues than equivalent nonhuman cues, and that the size of the cue is a critical element in determining dogs' success in following it. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Spatial cues more salient than color cues in cotton-top tamarins (Saguinus oedipus) reversal learning.

Animals living in stable home ranges have many potential cues to locate food. Spatial and color cues are important for wild Callitrichids (marmosets and tamarins). Field studies have assigned the highest priority to distal spatial cues for determining the location of food resources with color cues serving as a secondary cue to assess relative ripeness, once a food source is located. We tested two hypotheses with captive cotton-top tamarins: (a) Tamarins will demonstrate higher rates of initial learning when rewarded for attending to spatial cues versus color cues. (b) Tamarins will show higher rates of correct responses when transferred from color cues to spatial cues than from spatial cues to color cues. The results supported both hypotheses. Tamarins rewarded based on spatial location made significantly more correct choices and fewer errors than tamarins rewarded based on color cues during initial learning. Furthermore, tamarins trained on color cues showed significantly increased correct responses and decreased errors when cues were reversed to reward spatial cues. Subsequent reversal to color cues induced a regression in performance. For tamarins spatial cues appear more salient than color cues in a foraging task. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Chemosensory Orientation of the Rock Crab Cancer irroratus

The importance of chemical cues in the foraging behavior of the rock crab, Cancer irroratus, was investigated. Crabs were presented with mussel prey located upstream, downstream, or cross-stream. Trials were conducted under both light and dark conditions. With the prey upstream, the crabs exhibited the shortest search time and 100% searching success. There was a significant difference between flow direction treatments, but there were no significant differences between light and dark treatments. When presented with mussel extract and a seawater control, crabs approached the source of the current. Analysis of search patterns revealed differences in search time, path length and straightness, and total number of turns. Chemoreception was the predominant mode of prey detection and was used in guiding crabs to their prey. Large variabilities in the search path and search path parameters were exhibited, and there was no fixed search pattern for orientation toward food while foraging. It is suggested that rock crabs employed both chemotaxis and rheotaxis for locating odor sources.     

基于差分进化的改进细菌觅食算法在智能配电网故障定位方法中的应用

为了解决含分布式电源的配电网的故障定位问题,提出一种基于差分进化的改进细菌觅食算法进行配电网故障定位,首先针对分布式电源投切问题,构建能够动态适应多个分布式电源投切的开关函数,然后结合区域划分思想,通过将各个配网支路分为有源树和无源树进行故障信息筛选,降低解空间,提高故障定位的速度;同时针对细菌觅食算法精度不高和全局搜索能力较差的问题,借鉴差分进化中的变异和交叉机制,通过多样性控制与交叉操作协调来实现细菌觅食算法在细化搜索与扩展新区之间的协调,提高算法的寻优精度和全局寻优能力,适用于复杂的含分布式电源的配电网络。通过算例对该故障定位方法进行仿真,结果表明该算法能准确定位,并具有一定的有效性和容错性。     

人工蜂群算法综述

近年来群智能算法发展较为迅速并解决了很多大规模的复杂问题。人工蜂群算法是一种新型的群智能算法, 以其很强的全局收敛性、贪婪启发式的搜索特征以及求解问题的快速性等优越的性能受到广泛关注。简单介绍了人工蜂群算 法提出的生物学背景;由蜜蜂觅食行为与现实问题的求解类比给出了该算法的建模思想;并详细介绍了人工蜂群算法实现的 算法模型;从基于算法的改进以及基于算法的应用两方面讨论了近年来很多学者对人工蜂群算法研究的现状;最后对人工蜂群 算法的研究进行展望,从算法的弱点分析提出了该算法改进的方向以及进一步应用的领域。     

多策略改进的天鹰优化算法及其应用

为改善天鹰优化算法(aquila optimizer, AO)在求解复杂优化问题时存在易陷入局部最优等不足,提出一种多策略改进的天鹰优化算法(multi-strategy improved aquila optimizer, MIAO)。首先,提出镜像单纯形法策略扩大天鹰搜索范围,提升种群多样性和逃离桎梏能力;其次,在天鹰算法的X3阶段融入社会自由觅食策略,摆脱全局平均值的束缚,提升迭代后期天鹰个体的多样性;同时,将阶梯步进策略引入X4阶段,保证当前优势个体加快向全局最优前进的趋势,增加收敛速度;最后,改进原有开发机制,提升算法寻优能力。对10个常用基准函数以及CEC2017部分函数进行寻优实验,实验结果与Wilcoxon符号秩和检验结果均表明改进算法具有更好的寻优精度、收敛性能和稳定性。另外,通过一个机械优化设计实验进行测试分析,进一步验证所改进算法的优越性和实用性。     

Emission, reserve and economic load dispatch problem with non-smooth and non-convex cost functions using the hybrid bacterial foraging-Nelder-Mead algorithm

In this paper, a new approach is proposed to solve the economic load dispatch (ELD) problem. Power generation, spinning reserve and emission costs are simultaneously considered in the objective function of the proposed ELD problem. In this condition, if the valve-point effects of thermal units are considered in the proposed emission, reserve and economic load dispatch (ERELD) problem, a non-smooth and non-convex cost function will be obtained. Frequency deviation, minimum frequency limits and other practical constraints are also considered in this problem. For this purpose, ramp rate limit, transmission line losses, maximum emission limit for specific power plants or total power system, prohibited operating zones and frequency constraints are considered in the optimization problem. A hybrid method that combines the bacterial foraging (BF) algorithm with the Nelder-Mead (NM) method (called BF-NM algorithm) is used to solve the problem. In this study, the performance of the proposed BF-NM algorithm is compared with the performance of other classic (non-linear programming) and intelligent algorithms such as particle swarm optimization (PSO) as well as genetic algorithm (GA), differential evolution (DE) and BF algorithms. The simulation results show the advantages of the proposed method for reducing the total cost of the system.