Effects of predator chemical cues and behavioral biorhythms on foraging activity of terrestrial salamanders

Red-backed salamanders, Plethodon cinereus, show a variety of alarm responses to chemical cues from eastern garter snakes, Thamnophis sirtalis. We measured the foraging activity of red-backed salamanders exposed to water soiled by a garter snake (fed P. cinereus) or to unsoiled water. Salamanders exposed to snake-soiled water showed less foraging activity than salamanders exposed to unsoiled water; therefore, predators could have nonlethal effects on salamander populations. Our results also show additional factors influenced salamander foraging activity. Salamander foraging activity and responsiveness to chemical cues do not appear to have been affected by sex or food deprivation. Salamander foraging activity does appear to have been influenced by activity biorhythms. Foraging activity of animals in both treatments showed a bimodal periodicity that is consistent with natural activity patterns controlled by internal biorhythms. Exposure to snake-soiled water significantly reduced foraging activity during periods of peak foraging activity, but had a subtler effect0 on foraging activity during natural lulls in activity. We suggest that both activity biorhythms and exposure to chemical cues are important factors affecting salamander foraging behavior.     

Fitness-maximizing foragers can use information about patch quality to decide how to search for and within patches: optimal Lévy walk searching patterns from optimal foraging theory

Optimal foraging theory shows how fitness-maximizing foragers can use information about patch quality to decide how to search within patches. It is amply supported by empirical studies. Nonetheless, the theory largely ignores the fact that foragers may need to search for patches as well as for the targets within them. Here, using an exact but simple mathematical argument, it is shown how foragers can use information about patch quality to facilitate the execution of Lévy walk movement patterns with μ = 2 at inter-patch scales. These movement patterns are advantageous when searching for patches that are not depleted or rejected once visited but instead remain profitable. The analytical results are verified by the results of numerical simulations. The findings bring forth an innovative theoretical synthesis of searching for and within patches and, suggest that foragers'' memories may be adaptive under spatially heterogeneous reward schedules.     

Ambush frequency should increase over time during optimal predator search for prey

We advance and apply the mathematical theory of search games to model the problem faced by a predator searching for prey. Two search modes are available: ambush and cruising search. Some species can adopt either mode, with their choice at a given time traditionally explained in terms of varying habitat and physiological conditions. We present an additional explanation of the observed predator alternation between these search modes, which is based on the dynamical nature of the search game they are playing: the possibility of ambush decreases the propensity of the prey to frequently change locations and thereby renders it more susceptible to the systematic cruising search portion of the strategy. This heuristic explanation is supported by showing that in a new idealized search game where the predator is allowed to ambush or search at any time, and the prey can change locations at intermittent times, optimal predator play requires an alternation (or mixture) over time of ambush and cruise search. Thus, our game is an extension of the well-studied ‘Princess and Monster’ search game. Search games are zero sum games, where the pay-off is the capture time and neither the Searcher nor the Hider knows the location of the other. We are able to determine the optimal mixture of the search modes when the predator uses a mixture which is constant over time, and also to determine how the mode mixture changes over time when dynamic strategies are allowed (the ambush probability increases over time). In particular, we establish the ‘square root law of search predation’: the optimal proportion of active search equals the square root of the fraction of the region that has not yet been explored.     

Geometry, features, and panoramic views: Ants in rectangular arenas.

When tested in rectangular arenas, the navigational behavior of the ant Gigantiops destructor can produce results similar to vertebrates. Such results are usually interpreted as supporting the ability of animals to segregate spatial geometry and features. Here, we combine a detailed analysis of ants' paths with panoramic images taken from the ant's perspective that can serve as a basis for developing view-based matching models. The corner choices observed in ants were better predicted by the use of panoramic views along with a simple matching process [rotational image difference function (rIDF)] than by models assuming segregation of geometry and features (G/F). Our view-based matching model could also explain some aspects of the ants' path (i.e., initial direction, length) resulting from the different visual conditions, suggesting that ants were using such a taxon-like strategy. Analyzed at the individual level, the results show that ants' idiosyncratic paths tend to evolve gradually from trial to trial, revealing that the ants were partially updating their route memory after each trial. This study illustrates the remarkable flexibilities that can arise from the use of taxon-like strategies and stresses the importance of considering them in vertebrates. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

改进细菌觅食算法求解柔性作业车间调度问题

针对柔性作业车间调度问题的NP难特性,提出一种改进的细菌觅食优化算法。采用集成法策略同时求解柔性作业车间调度问题的机器分配和工序调度子问题。将细菌个体表示为工序串,建立问题和算法的映射关系;分别针对普通细菌个体和当前最优个体设计了多重趋化操作,以增强算法的局部搜索能力;复制操作设置繁殖阈和死亡阈,以提高对历史经验的继承程度;迁移/驱散操作中,结合改进的LPT启发式规则,提出带倾向性的迁移/驱散操作方式。采用正交试验对算法的重要参数进行了优化配置,通过搜索算子优化效果对比实验证明了正交试验的结论;进行了收敛性能对比实验,证明算法具有优秀的全局开发能力和局部探索能力;典型算例实验结果表明,该算法能够有效求解柔性作业车间调度问题。     

基于车辆时空状态链的电动汽车充换电需求模型

随着电动汽车普及,充换电设施网络整体规划建设已成为电动汽车产业发展的重要环节。整体考虑充电需求与换电需求,提出一种基于出行时空状态链的电动汽车充换电需求模型。首先,通过分析车辆行驶与停留多状态间相互转换过程,定义车辆出行时间链与空间链的特征量,并设计车辆状态转移矩阵。然后根据多种充换电模式,以及温度对单位里程耗电量影响,构建电动汽车充换电需求模型。最后,提出基于自适应混合细菌觅食算法,计算车辆处于充电需求时,多种充电模式选取情况。算例分析表明,该模型可以准确模拟用户出行规律,体现电动汽车在行驶与停留多状态下的充换电需求时空分布特点。     

Uncertainty drives deviations in normative foraging decision strategies

Nearly all animals forage to acquire energy for survival through efficient search and resource harvesting. Patch exploitation is a canonical foraging behaviour, but there is a need for more tractable and understandable mathematical models describing how foragers deal with uncertainty. To provide such a treatment, we develop a normative theory of patch foraging decisions, proposing mechanisms by which foraging behaviours emerge in the face of uncertainty. Our model foragers statistically and sequentially infer patch resource yields using Bayesian updating based on their resource encounter history. A decision to leave a patch is triggered when the certainty of the patch type or the estimated yield of the patch falls below a threshold. The time scale over which uncertainty in resource availability persists strongly impacts behavioural variables like patch residence times and decision rules determining patch departures. When patch depletion is slow, as in habitat selection, departures are characterized by a reduction of uncertainty, suggesting that the forager resides in a low-yielding patch. Uncertainty leads patch-exploiting foragers to overharvest (underharvest) patches with initially low (high) resource yields in comparison with predictions of the marginal value theorem. These results extend optimal foraging theory and motivate a variety of behavioural experiments investigating patch foraging behaviour.     

Automatic generation control of a multi area hydrothermal system using reinforced learning neural network controller

This paper deals with automatic generation control (AGC) of a three unequal area hydrothermal system. Reheat turbines in thermal areas and electric governor in hydro area are considered. Appropriate generation rate constraints are considered in the areas. Bacterial foraging (BF) technique is used to simultaneously optimize the integral gains (K_Ii) and speed regulation parameter (R_i) keeping frequency bias fixed at frequency response characteristics. The integral controller in this case is termed as BFIC. The performance of a multilayer perception neural network (MLPNN) controller using reinforcement learning is evaluated for the system. In this reinforcement learning, the weights are dynamically adjusted online using backpropagation algorithm with error being the area control error (ACE). The performance of the MLPNN controller is compared with that of BFIC. Also, the performance of MLPNN controller over a wide range of system loading conditions and step load perturbations is compared with BFIC. Investigations clearly reveal the superior performance of MLPNN controller over BFIC. Sensitivity analysis subject to wide changes in system loading, inertia constant (H) and size and location of step load perturbation is carried out to investigate the robustness of the controller with the optimum K_Ii and R_i obtained at nominal condition.     

考虑配电网结构变化的DG规划

为了更合理地将分布式电源并入配电网中,提出考虑配网结构变化影响的DG规划。首先采用损耗灵敏度因子对DG进行最优布置,然后建立了以最大减少系统网损为目标的网络重构与DG容量配置的综合优化模型,并通过改进的细菌觅食算法对所提模型进行求解,最后用IEEE33和IEEE69节点系统进行仿真计算。计算结果表明,考虑配电网结构变化的DG规划更加实际、有效。     

风险调度中引入知识迁移的细菌觅食强化学习优化算法

针对电力系统运行过程中负荷及故障的不确定性,在经济调度中引入风险评估原理,并提出了一种全新的基于知识迁移的细菌觅食强化学习优化算法。该算法将细菌觅食算法的寻优模式与Q学习算法的试错迭代机制结合,利用多主体协同合作来更新共有的知识矩阵,并以基于知识延伸的维度缩减方式避免了"维数灾难"。在预学习获得最优知识矩阵后,利用知识迁移加速在线学习进程。IEEE RTS-79测试系统的仿真结果表明:所提算法在保证获得高质量最优解的同时,寻优速度可达经典智能算法的9~20倍,适合求解大规模复杂电网的风险调度快速优化。