Asymptotic flocking dynamics for the kinetic Cucker-Smale model

In this paper, we analyse the asymptotic behavior of solutions of the continuous kinetic version of flocking by Cucker and Smale [16], which describes the collective behavior of an ensemble of organisms, animals or devices. This kinetic version introduced in [24] is here obtained starting from a Boltzmann-type equation. The large-time behavior of the distribution in phase space is subsequently studied by means of particle approximations and a stability property in distances between measures. A continuous analogue of the theorems of [16] is shown to hold for the solutions on the kinetic model. More precisely, the solutions will concentrate exponentially fast their velocity to their mean while in space they will converge towards a translational flocking solution.

Flocking behaviour: Agent-based simulation and hierarchical leadership.

We have studied how leaders emerge in a group as a consequence of interactions among its members. We propose that leaders can emerge as a consequence of a self-organized process based on local rules of dyadic interactions among individuals. Flocks are an example of self-organized behaviour in a group and properties similar to those observed in flocks might also explain some of the dynamics and organization of human groups. We developed an agent-based model that generated flocks in a virtual world and implemented it in a multi-agent simulation computer program that computed indices at each time step of the simulation to quantify the degree to which a group moved in a coordinated way (index of flocking behaviour) and the degree to which specific individuals led the group (index of hierarchical leadership). We ran several series of simulations in order to test our model and determine how these indices behaved under specific agent and world conditions. We identified the agent, world property, and model parameters that made stable, compact flocks emerge, and explored possible environmental properties that predicted the probability of becoming a leader.

Opportunities for improvements in flocking models

Flocking is the capacity of coherent movement between multiple animals, including birds. Prominent research into flocking is presented. Particle Swarm Optimisation (PSO) has been the prominent result from research into flocking. It is considered that opportunities for further research in flocking exist. With the potential for automated traffic systems, it is concluded that flocking should be reinvestigated for this purpose.

Experimental analysis of the Reynolds flocking model

The classic Reynolds flocking model is formally analysed, with results presented and discussed. Flocking behaviour was investigated through the development of two measurements of flocking, flock area and polarisation, with a view to applying the findings to robotic applications. Experiments varying the flocking simulation parameters individually and simultaneously provide new insight into the control of flock behaviour.

Using an individual-based model to select among alternative foraging strategies of woodpigeons: data support a memory-based model with a flocking mechanism

Population modelling is increasingly recognised as a useful tool for pesticide risk assessment. For vertebrates that may ingest pesticides with their food, such as woodpigeon (Columba palumbus), population models that simulate foraging behaviour explicitly can help predicting both exposure and population-level impact. Optimal foraging theory is often assumed to explain the individual-level decisions driving distributions of individuals in the field, but it may not adequately predict spatial and temporal characteristics of woodpigeon foraging because of the woodpigeons’ excellent memory, ability to fly long distances, and distinctive flocking behaviour. Here we present an individual-based model (IBM) of the woodpigeon. We used the model to predict distributions of foraging woodpigeons that use one of six alternative foraging strategies: optimal foraging, memory-based foraging and random foraging, each with or without flocking mechanisms. We used pattern-oriented modelling to determine which of the foraging strategies is best able to reproduce observed data patterns. Data used for model evaluation were gathered during a long-term woodpigeon study conducted between 1961 and 2004 and a radiotracking study conducted in 2003 and 2004, both in the UK, and are summarised here as three complex patterns: the distributions of foraging birds between vegetation types during the year, the number of fields visited daily by individuals, and the proportion of fields revisited by them on subsequent days. The model with a memory-based foraging strategy and a flocking mechanism was the only one to reproduce these three data patterns, and the optimal foraging model produced poor matches to all of them. The random foraging strategy reproduced two of the three patterns but was not able to guarantee population persistence. We conclude that with the memory-based foraging strategy including a flocking mechanism our model is realistic enough to estimate the potential exposure of woodpigeons to pesticides. We discuss how exposure can be linked to our model, and how the model could be used for risk assessment of pesticides, for example predicting exposure and effects in heterogeneous landscapes planted seasonally with a variety of crops, while accounting for differences in land use between landscapes.

Airport Bird Threat in North America from Large Flocking Birds (geese) (as Viewed by an Engine Manufacturer)--Part 1

In worldwide aviation operations, bird collisions with aircraft and ingestions into engine inlets present safety hazards and financial loss through equipment damage, loss of service and disruption to operations. The problem is encountered by all types of aircraft, both military and commercial. Modern aircraft engines have achieved a high level of reliability while manufacturers and users continually strive to further improve the safety record. A major safety concern today includes common-cause events which involve significant power loss on more than one engine. These are externally-inflicted occurrences, with the most frequent being encounters with flocks of birds. Most frequently these encounters occur during flight operations in the area on or near airports, near the ground instead of at cruise altitude conditions. This paper focuses on the increasing threat to aircraft and engines posed by the recorded growth in geese populations in North America. Service data show that goose strikes are increasing, especially in North America, consistent with the growing resident geese populations estimated by the United States Department of Agriculture (USDA). Airport managers, along with the governmental authorities, need to develop a strategy to address this large flocking bird issue. This paper also presents statistics on the overall status of the bird threat for birds of all sizes in North America relative to other geographic regions. Overall, the data shows that Canada and the USA have had marked improvements in controlling the threat from damaging birds - except for the increase in geese strikes. To reduce bird ingestion hazards, more aggressive corrective measures are needed in international air transport to reduce the chances of serious incidents or accidents from bird ingestion encounters. Air transport authorities must continue to take preventative and avoidance actions to counter the threat of birdstrikes to aircraft. The primary objective of this paper is to increase awareness of, and focus attention on, the safety hazards presented by large flocking birds such as geese. In the worst case, multiple engine power loss due to large bird ingestion could result in an off-airport forced landing accident. Hopefully, such awareness will prompt governmental regulatory agencies to address the hazards associated with growing populations of geese in North America.

Introducing the fractional-order Darwinian PSO

One of the most well-known bio-inspired algorithms used in optimization problems is the particle swarm optimization (PSO), which basically consists on a machinelearning technique loosely inspired by birds flocking in search of food. More specifically, it consists of a number of particles that collectively move on the search space in search of the global optimum. The Darwinian particle swarm optimization (DPSO) is an evolutionary algorithm that extends the PSO using natural selection, or survival of the fittest, to enhance the ability to escape from local optima. This paper firstly presents a survey on PSO algorithms mainly focusing on the DPSO. Afterward, a method for controlling the convergence rate of the DPSO using fractional calculus (FC) concepts is proposed. The fractional-order optimization algorithm, denoted as FO-DPSO, is tested using several well-known functions, and the relationship between the fractional-order velocity and the convergence of the algorithm is observed. Moreover, experimental results show that the FO-DPSO significantly outperforms the previously presented FO-PSO.

Crossing genetic and swarm intelligence algorithms to generate logic circuits

Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. On the other hand, Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as GAs. The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. PSO is attractive because there are few parameters to adjust. This paper presents hybridization between a GA algorithm and a PSO algorithm (crossing the two algorithms). The resulting algorithm is applied to the synthesis of combinational logic circuits. With this combination is possible to take advantage of the best features of each particular algorithm.

Mechanosensory interactions drive collective behaviour in Drosophila.

Collective behaviour enhances environmental sensing and decision-making in groups of animals. Experimental and theoretical investigations of schooling fish, flocking birds and human crowds have demonstrated that simple interactions between individuals can explain emergent group dynamics. These findings indicate the existence of neural circuits that support distributed behaviours, but the molecular and cellular identities of relevant sensory pathways are unknown. Here we show that Drosophila melanogaster exhibits collective responses to an aversive odour: individual flies weakly avoid the stimulus, but groups show enhanced escape reactions. Using high-resolution behavioural tracking, computational simulations, genetic perturbations, neural silencing and optogenetic activation we demonstrate that this collective odour avoidance arises from cascades of appendage touch interactions between pairs of flies. Inter-fly touch sensing and collective behaviour require the activity of distal leg mechanosensory sensilla neurons and the mechanosensory channel NOMPC. Remarkably, through these inter-fly encounters, wild-type flies can elicit avoidance behaviour in mutant animals that cannot sense the odour--a basic form of communication. Our data highlight the unexpected importance of social context in the sensory responses of a solitary species and open the door to a neural-circuit-level understanding of collective behaviour in animal groups.

05040-015 Viking Lake Watershed Final Report

Viking Lake State Park is beautiful resource which has been special to residents of Southwest Iowa and visitors from around the region. Unfortunately, Viking Lake itself is being impacted by non-point source pollution. Water quality conditions are becoming the reason that visitors are shying away from the park instead of flocking to it. To combat these non-point source problems the Viking Lake Water Quality Project has been initiated and $327,000 has been allocated through the Section 319/WSPF Program which will address water quality concerns in the watershed. Additionally, IDNR Fisheries is preparing for an entire renovation of Viking Lake in 2006. One funding gap remains, that may prevent this comprehensive water quality project from achieving a successful endpoint. Funds are still needed for the renovation of malfunctioning septic systems at Viking Village housing development which is adjacent to the park, and has been identified as a primary source of contamination entering the lake. The intent of this application is to secure funds so that these septic system problems can be corrected and water quality conditions of this important natural resource restored for public enjoyment.

Particle swarm optimization for two-connected networks with bounded rings

The Two-Connected Network with Bounded Ring (2CNBR) problem is a network design problem addressing the connection of servers to create a survivable network with limited redirections in the event of failures. Particle Swarm Optimization (PSO) is a stochastic population-based optimization technique modeled on the social behaviour of flocking birds or schooling fish. This thesis applies PSO to the 2CNBR problem. As PSO is originally designed to handle a continuous solution space, modification of the algorithm was necessary in order to adapt it for such a highly constrained discrete combinatorial optimization problem. Presented are an indirect transcription scheme for applying PSO to such discrete optimization problems and an oscillating mechanism for averting stagnation.

Generating Aesthetically Pleasing Images in a Virtual Environment using Particle Swarm Optimization

This research focuses on generating aesthetically pleasing images in virtual environments using the particle swarm optimization (PSO) algorithm. The PSO is a stochastic population based search algorithm that is inspired by the flocking behavior of birds. In this research, we implement swarms of cameras flying through a virtual world in search of an image that is aesthetically pleasing. Virtual world exploration using particle swarm optimization is considered to be a new research area and is of interest to both the scientific and artistic communities. Aesthetic rules such as rule of thirds, subject matter, colour similarity and horizon line are all analyzed together as a multi-objective problem to analyze and solve with rendered images. A new multi-objective PSO algorithm, the sum of ranks PSO, is introduced. It is empirically compared to other single-objective and multi-objective swarm algorithms. An advantage of the sum of ranks PSO is that it is useful for solving high-dimensional problems within the context of this research. Throughout many experiments, we show that our approach is capable of automatically producing images satisfying a variety of supplied aesthetic criteria.

Interaction and Intelligent Behavior

We introduce basic behaviors as primitives for control and learning in situated, embodied agents interacting in complex domains. We propose methods for selecting, formally specifying, algorithmically implementing, empirically evaluating, and combining behaviors from a basic set. We also introduce a general methodology for automatically constructing higher--level behaviors by learning to select from this set. Based on a formulation of reinforcement learning using conditions, behaviors, and shaped reinforcement, out approach makes behavior selection learnable in noisy, uncertain environments with stochastic dynamics. All described ideas are validated with groups of up to 20 mobile robots performing safe--wandering, following, aggregation, dispersion, homing, flocking, foraging, and learning to forage.

From the Hill

Q&A: Personal loss leads to role as leading advocate of nonviolence in South Africa Business-Ready: Entrepreneurial Alliance has students flocking to the drawing board A Hand Up: Alumni consultants organize to give small businesses a boost Child's Play: Shelley Wollert wants kids to clamor for Elska, a musical, magical friend Poems that Explore "A World of Haunting Absences" A History of Putting a Spin on Vigilante Justice Old Glories Recent Releases Gardner Colby's Remarkable Mom Joining the Club: Ex-refugees, Somali boys have big impact on elite soccer team Hard Hitter: In the chemistry lab and on the field, John Gilboy Is "a no-quit kind of guy" Ravens assistant GM DeCosta Prepares for Future Role Scouting the NFL D-I Vet MacDonald Takes Over Men's Hockey