Foundations of Computational Intelligence Volume 3: Global Optimization

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SDS is both an efficient and robust global search and optimisation algorithm, which has been extensively mathematically described. Ant colony optimization ACO , introduced by Dorigo in his doctoral dissertation, is a class of optimization algorithms modeled on the actions of an ant colony. ACO is a probabilistic technique useful in problems that deal with finding better paths through graphs.

Artificial 'ants'—simulation agents—locate optimal solutions by moving through a parameter space representing all possible solutions. Natural ants lay down pheromones directing each other to resources while exploring their environment. The simulated 'ants' similarly record their positions and the quality of their solutions, so that in later simulation iterations more ants locate for better solutions. Particle swarm optimization PSO is a global optimization algorithm for dealing with problems in which a best solution can be represented as a point or surface in an n-dimensional space.

Hypotheses are plotted in this space and seeded with an initial velocity , as well as a communication channel between the particles. Over time, particles are accelerated towards those particles within their communication grouping which have better fitness values. The main advantage of such an approach over other global minimization strategies such as simulated annealing is that the large number of members that make up the particle swarm make the technique impressively resilient to the problem of local minima.

Swarm Intelligence-based techniques can be used in a number of applications. The U. The European Space Agency is thinking about an orbital swarm for self-assembly and interferometry. NASA is investigating the use of swarm technology for planetary mapping. A paper by M. Anthony Lewis and George A. Bekey discusses the possibility of using swarm intelligence to control nanobots within the body for the purpose of killing cancer tumors.

The use of swarm intelligence in telecommunication networks has also been researched, in the form of ant-based routing. This was pioneered separately by Dorigo et al.

Reinforcement of the route in the forwards, reverse direction and both simultaneously have been researched: backwards reinforcement requires a symmetric network and couples the two directions together; forwards reinforcement rewards a route before the outcome is known but then one would pay for the cinema before one knows how good the film is.

As the system behaves stochastically and is therefore lacking repeatability, there are large hurdles to commercial deployment.

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Mobile media and new technologies have the potential to change the threshold for collective action due to swarm intelligence Rheingold: , P The location of transmission infrastructure for wireless communication networks is an important engineering problem involving competing objectives. A minimal selection of locations or sites are required subject to providing adequate area coverage for users. A very different-ant inspired swarm intelligence algorithm, stochastic diffusion search SDS , has been successfully used to provide a general model for this problem, related to circle packing and set covering.

It has been shown that the SDS can be applied to identify suitable solutions even for large problem instances. Airlines have also used ant-based routing in assigning aircraft arrivals to airport gates. At Southwest Airlines a software program uses swarm theory, or swarm intelligence—the idea that a colony of ants works better than one alone. Each pilot acts like an ant searching for the best airport gate. Lawson explains. As a result, the "colony" of pilots always go to gates they can arrive at and depart from quickly.

The program can even alert a pilot of plane back-ups before they happen.

Multiswarm Particle Swarm Optimization with Transfer of the Best Particle

Artists are using swarm technology as a means of creating complex interactive systems or simulating crowds. Stanley and Stella in: Breaking the Ice was the first movie to make use of swarm technology for rendering, realistically depicting the movements of groups of fish and birds using the Boids system.

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Tim Burton's Batman Returns also made use of swarm technology for showing the movements of a group of bats. The Lord of the Rings film trilogy made use of similar technology, known as Massive , during battle scenes. Swarm technology is particularly attractive because it is cheap, robust, and simple.

Airlines have used swarm theory to simulate passengers boarding a plane. Southwest Airlines researcher Douglas A. Lawson used an ant-based computer simulation employing only six interaction rules to evaluate boarding times using various boarding methods. Miller, , xii-xviii. Medical Use of Human Swarming—in , Stanford University School of Medicine and Unanimous AI published studies showing that groups of human doctors, when connected together by real-time swarming algorithms, could diagnose medical conditions with substantially higher accuracy than individual doctors or groups of doctors working together using traditional crowd-sourcing methods.

Swarm grammars are swarms of stochastic grammars that can be evolved to describe complex properties such as found in art and architecture. Such behavior can also suggest deep learning algorithms, in particular when mapping of such swarms to neural circuits is considered. In a series of works al-Rifaie et al. The resulting hybrid algorithm is used to sketch novel drawings of an input image, exploiting an artistic tension between the local behaviour of the 'birds flocking'—as they seek to follow the input sketch—and the global behaviour of the "ants foraging"—as they seek to encourage the flock to explore novel regions of the canvas.

Global Optimization of MINLP by Evolutionary Algorithms

The "creativity" of this hybrid swarm system has been analysed under the philosophical light of the "rhizome" in the context of Deleuze 's "Orchid and Wasp" metaphor. In a more recent work of al-Rifaie et al. Once the attention of the swarm is drawn to a certain line within the canvas, the capability of PSO is used to produce a 'swarmic sketch' of the attended line. The swarms move throughout the digital canvas in an attempt to satisfy their dynamic roles—attention to areas with more details—associated to them via their fitness function.

Having associated the rendering process with the concepts of attention, the performance of the participating swarms creates a unique, non-identical sketch each time the 'artist' swarms embark on interpreting the input line drawings. In a similar work, "Swarmic Paintings and Colour Attention", [57] non-photorealistic images are produced using SDS algorithm which, in the context of this work, is responsible for colour attention. The "computational creativity" of the above-mentioned systems are discussed in [54] [58] [59] through the two prerequisites of creativity i.

Michael Theodore and Nikolaus Correll use swarm intelligent art installation to explore what it takes to have engineered systems to appear lifelike. From Wikipedia, the free encyclopedia. See also: Swarm behaviour. Main article: Boids. Main article: Self-propelled particles. See also: List of metaphor-based metaheuristics. Main article: Stochastic diffusion search.

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Main article: Ant colony optimization. Main article: Particle swarm optimization. This article's use of external links may not follow Wikipedia's policies or guidelines. Please improve this article by removing excessive or inappropriate external links, and converting useful links where appropriate into footnote references.

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Artificial immune systems Collaborative intelligence Collective effervescence Group mind science fiction Cellular automaton Complex systems Differential evolution Dispersive flies optimisation Evolutionary computation Global brain Harmony search Harris hawks optimization Multi-agent system Myrmecology Promise theory Quorum sensing Population protocol Reinforcement learning Rule Self-organized criticality Spiral optimization algorithm Stochastic optimization Swarm Development Group Swarm robotic platforms Swarming SwisTrack Symmetry breaking of escaping ants The Wisdom of Crowds Wisdom of the crowd.

Flocks, herds and schools: A distributed behavioral model.

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Content Type. Bishop, Convergence analysis of stochastic diffusion search, Journal of Parallel Algorithms and Applications, vol. While many such architectures are too complex to be optimized by hand, neuroevolution can be used to do so automatically. New York: Avery. In this talk we first focus on a capital issue: smart mobility. Wang, X.

Association for Computing Machinery. Part I: background and development". Natural Computing.

Citation Styles for "Foundations of computational intelligence. Volume 3, Global optimization"

Physical Review Letters. Bibcode : PhRvL.. Computer Graphics. Physica A. Bibcode : PhyA.. Bibcode : Sci Annals of Physics. Bibcode : AnPhy.

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Bibcode : JPhA Physica D: Nonlinear Phenomena. Bibcode : PhyD.. GECCO ' Neural Computation '98, pp.

Anthony; Bekey, George A. IEEE, Machine Learning. An agent based approach to site selection for wireless networks. Science Daily. Yet his book will not only help test personnel to improve effectivity, it will also serve as a way to improve efficiency through its strong focus on reuse. This makes TestFrame the practical guide to testing information systems for everyone involved in software testing test developers, test managers, and staff charged with quality assurance. We will send you an SMS containing a verification code.

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