Convergence results for stochastic particle systems with social interaction

We consider stochastic individual-based models for social behaviour of groups of animals. In these models the trajectory of each animal is given by a stochastic differential equation with interaction. The social interaction is contained in the drift term of the SDE. We consider a global aggregation force and a short-range repulsion force. The repulsion range and strength gets rescaled with the number of animals N. We show that for N tending to infinity stochastic fluctuations disappear and a smoothed version of the empirical process converges uniformly towards the solution of a nonlinear, nonlocal partial differential equation of advection-reaction-diffusion type. The rescaling of the repulsion in the individual-based model implies that the corresponding term in the limit equation is local while the aggregation term is non-local. Moreover, we discuss the effect of a predator on the system and derive an analogous convergence result. The predator acts as an repulsive force. Different laws of motion for the predator are considered.

Particle swarm optimization: dynamical analysis through fractional calculus

This chapter considers the particle swarm optimization algorithm as a system, whose dynamics is studied from the point of view of fractional calculus. In this study some initial swarm particles are randomly changed, for the system stimulation, and its response is compared with a non-perturbed reference response. The perturbation effect in the PSO evolution is observed in the perspective of the fitness time behaviour of the best particle. The dynamics is represented through the median of a sample of experiments, while adopting the Fourier analysis for describing the phenomena. The influence upon the global dynamics is also analyzed. Two main issues are reported: the PSO dynamics when the system is subjected to random perturbations, and its modelling with fractional order transfer functions.

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.

Optimisation of a fermentation process for butanol production by particle swarm optimisation (PSO)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Division of labour in a group of agents inspired by ants' foraging behaviour

Questa tesi prende spunto da altri studi realizzati nel campo delle esattamente nel campo delle “Swam Intelligence”, una branca delle intelligenze artificiali prende spunto dal comportamento di animali sociali, sopratutto insetti come termini, formiche ed api, per trarne interessanti metafore per la creazione di algoritmi e tecniche di programmazione. Questo tipo di algoritmi, come per gli esempi tratti dalla biologia, risultano dotati di interessanti proprietà adatte alla risoluzione di certi problemi nell'ambito dell'ingegneria. Lo scopo della tesi è quello di mostrare tramite un esempio pratico le proprietà dei sistemi sviluppati tramite i principi delle Swarm Intelligence, evidenziando la flessibilità di questi sistemi. Nello specifico, la mia tesi analizzerà il problema della suddivisione del lavoro in una colonia di formiche, fornendo un esempio pratico quale il compito di cattura di prede in un determinato ambiente. Ho sviluppato un'applicazione software in Java che simula tale comportamento, i dati utilizzati durante le diverse simulazioni possono essere modificati tramite file di testo, in modo da ottenere risultati validi per diversi contesti.

Coordination and Control of Autonomous Mobile Robots Swarms by using Particle Swarm Optimization Algorithm and Consensus Theory

This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.

Virtual sensing technology applied to a swarm of autonomous robots.

This thesis proposes a novel technology in the field of swarm robotics that allows a swarm of robots to sense a virtual environment through virtual sensors. Virtual sensing is a desirable and helpful technology in swarm robotics research activity, because it allows the researchers to efficiently and quickly perform experiments otherwise more expensive and time consuming, or even impossible. In particular, we envision two useful applications for virtual sensing technology. On the one hand, it is possible to prototype and foresee the effects of a new sensor on a robot swarm, before producing it. On the other hand, thanks to this technology it is possible to study the behaviour of robots operating in environments that are not easily reproducible inside a lab for safety reasons or just because physically infeasible. The use of virtual sensing technology for sensor prototyping aims to foresee the behaviour of the swarm enhanced with new or more powerful sensors, without producing the hardware. Sensor prototyping can be used to tune a new sensor or perform performance comparison tests between alternative types of sensors. This kind of prototyping experiments can be performed through the presented tool, that allows to rapidly develop and test software virtual sensors of different typologies and quality, emulating the behaviour of several hardware real sensors. By investigating on which sensors is better to invest, a researcher can minimize the sensors’ production cost while achieving a given swarm performance. Through augmented reality, it is possible to test the performance of the swarm in a desired virtual environment that cannot be set into the lab for physical, logistic or economical reasons. The virtual environment is sensed by the robots through properly designed virtual sensors. Virtual sensing technology allows a researcher to quickly carry out real robots experiment in challenging scenarios without all the required hardware and environment.

The Optimal combination: Grammatical Swarm, Particle Swarm Optimization and Neural Networks.

Social behaviour is mainly based on swarm colonies, in which each individual shares its knowledge about the environment with other individuals to get optimal solutions. Such co-operative model differs from competitive models in the way that individuals die and are born by combining information of alive ones. This paper presents the particle swarm optimization with differential evolution algorithm in order to train a neural network instead the classic back propagation algorithm. The performance of a neural network for particular problems is critically dependant on the choice of the processing elements, the net architecture and the learning algorithm. This work is focused in the development of methods for the evolutionary design of artificial neural networks. This paper focuses in optimizing the topology and structure of connectivity for these networks.

Polynomial approximation using particle swarm optimization of lineal enhanced neural networks with no hidden layers.

This paper presents some ideas about a new neural network architecture that can be compared to a Taylor analysis when dealing with patterns. Such architecture is based on lineal activation functions with an axo-axonic architecture. A biological axo-axonic connection between two neurons is defined as the weight in a connection in given by the output of another third neuron. This idea can be implemented in the so called Enhanced Neural Networks in which two Multilayer Perceptrons are used; the first one will output the weights that the second MLP uses to computed the desired output. This kind of neural network has universal approximation properties even with lineal activation functions. There exists a clear difference between cooperative and competitive strategies. The former ones are based on the swarm colonies, in which all individuals share its knowledge about the goal in order to pass such information to other individuals to get optimum solution. The latter ones are based on genetic models, that is, individuals can die and new individuals are created combining information of alive one; or are based on molecular/celular behaviour passing information from one structure to another. A swarm-based model is applied to obtain the Neural Network, training the net with a Particle Swarm algorithm.

Behaviour of oligodendrocytes and Schwann cells in an experimental model of toxic demyelination of the central nervous system

Oligodendrocytes and Schwann cells are engaged in myelin production, maintenance and repairing respectively in the central nervous system (CNS) and the peripheral nervous system (PNS). Whereas oligodendrocytes act only within the CNS, Schwann cells are able to invade the CNS in order to make new myelin sheaths around demyelinated axons. Both cells have some limitations in their activities, i.e. oligodendrocytes are post-mitotic cells and Schwann cells only get into the CNS in the absence of astrocytes. Ethidium bromide (EB) is a gliotoxic chemical that when injected locally within the CNS, induce demyelination. In the EB model of demyelination, glial cells are destroyed early after intoxication and Schwann cells are free to approach the naked central axons. In normal Wistar rats, regeneration of lost myelin sheaths can be achieved as early as thirteen days after intoxication; in Wistar rats immunosuppressed with cyclophosphamide the process is delayed and in rats administered cyclosporine it may be accelerated. Aiming the enlightening of those complex processes, all events concerning the myelinating cells in an experimental model are herein presented and discussed.

Behaviour of albino and melanic variants of Biomphalaria glabrata Say, 1818 (Mollusca: Planorbidae) following infection by Schistosoma mansoni Sambon, 1907

The behaviour of the albino and melanic variants of Biomphalaria glabrata of Belo Horizonte (MG. Brazil) was studied comparatively, in terms of their respective susceptibilities to infection by Schistosoma mansoni of the same origin, through observation of the elimination of cercariae for a three-month period and the calculation of mortality and infection rates, in control and in infected snails. The number of amoebocytes, granulocytes and hyalinocytes in the circulating hemolymph during different periods of infection was analyzed. The evolution of the infection in the tissues was observed by means of histological cross-sections. The melanic variant showed greater susceptibility to infection and a higher mortality rate. The albino variant showed a higher number of circulating amoebocytes, both granulocytes and hyalinocytes. A higher number of degenerated sporocysts were seen in the histological cross-sections of the albino variant. The results suggest that the melanic variant of B. glabrata was more susceptible to infection by S. mansoni than was the albino variant.

Food profitability affects intranidal recruitment behaviour in the stingless bee Nannotrigona testaceicornis

Does the food's sugar concentration affect recruitment behaviour in the stingless bee Nan-notrigona testaceicornis? We recorded intranidal forager behaviour while offering sugar water of constant, increasing, or decreasing concentrations. Running speed was not correlated with sugar concentration but the jostling contacts/sec were. Food profitability also affected the recruiter's thorax vibrations: Pulse duration and duty cycle followed both concentration increases and decreases. Sugar concentration also influenced the number of recruited bees. In comparison to the phylogenetically closely related Scaptotrigona, Nan-notrigona's intranidal recruitment behaviour showed a more elaborate association with food profitability. This is likely to reflect differences in ecology and foraging strategies as Nannotrigona - in contrast to Scaptotrigona - does not lay scent trails to guide recruits to a food source.

Contrasting photoelectrochemical behaviour of two isomeric supramolecular dyes based on meso-tetra(pyridyl)porphyrin incorporating four (mu(3)-oxo)- triruthenium(III) clusters

A saddle shaped tetracluster porphyrin species containing four [Ru(3)O(OAc)(6)(py)(2)](+) clusters coordinated to the N-pyridyl atoms of 5,10,15,20-tetra(3-pyridyl)porphyrin, H(2)(3-TCPyP), has been investigated in comparison with the planar tetra(4-pyridyl) porphyrin analogue H(2)(4-TCPyP). The steric effects from the bulky peripheral complexes play a critical role in the H(2)(3-TCPyP) species, determining a non-planar configuration around the porphyrin centre and precluding any significant pi-electronic coupling, in contrast with the less hindered H(2)(4-TCPyP) species. Both systems exhibit a photoelectrochemical response in the presence of nanocrystalline TiO(2) films, involving the porphyrin excitation around 450 nm. However, only in the H(2)(4-TCPyP) case do the cluster moieties also contribute to the photoinduced electron injection process at 670 nm, reflecting the relevance of the electronic coupling between the porphyrin centre and the peripheral complexes.

Behaviour of biofuel addition on metallurgical properties of sinter

Blast furnace gas yield is essentially controlled by a gas-solid reaction phenomenon, which strongly influences hot metal manufacturing costs. As a result of rising prices for reducing agents on the international market, Companhia Siderurgica Nacional decided to inject natural gas into its blast furnaces. With more gas inside the furnace, the burden permeability became even more critical. To improve blast furnace gas yield, a new technological approach was adopted; raising the metallic burden reaction surface. To that end, a special sinter was developed with permeability being controlled by adding micropore nucleus forming agents, cellulignin coal, without, however, degrading its mechanical properties. This paper shows the main process parameters and the results from physicochemical characterisation of a sinter with controlled permeability, on a pilot scale, compared to those of conventional sinter. Gas flow laboratory simulations have conclusively corroborated the positive effects of micropore nucleus forming agents on enhancing sinter permeability.

Wetting behaviour of silicon nitride ceramics by Ti-Cu alloys

The wetting of Ti-Cu alloys on Si3N4 was analyzed by the sessile drop method, using an imaging system with a CCD camera during the heating under argon flow. The contact angle was measured as a function of temperature and time. The samples were cut transversally and characterized by scanning electron microscopy and energy dispersive spectrometry (SEM/EDS). Wettability of the Ti-Cu alloy on Si3N4 is influenced by the reaction between the Ti and the ceramic. The TC1 and TC2 alloys presented low final contact angle values around 2 degrees and 26 degrees, respectively, indicating good wetting on Si3N4. (c) 2006 Elsevier Ltd and Techna Group S.r.l. All rights reserved.