# 2011 IEEE Symposium on Swarm Intelligence

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Displaying Results 1 - 25 of 38
• ### [Front cover]

Publication Year: 2011, Page(s): c1
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Publication Year: 2011, Page(s): 1
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Publication Year: 2011, Page(s):iii - vi
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• ### SIS 2011 committee

Publication Year: 2011, Page(s):vii - ix
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• ### Scalability of a heterogeneous particle swarm optimizer

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (10)
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Most particle swarm optimization (PSO) algorithms maintain swarms of homogeneous particle, where all of the particles in the swarm follow the same behavior as specified via the particle position and velocity update rules. Many different position and velocity update rules have been developed, exhibiting different exploration - exploitation finger prints. Recently, a heterogeneous PSO (HPSO) has bee... View full abstract»

• ### Heterogeneous particle swarms in dynamic environments

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (7)
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This paper investigates the performance of a dynamic heterogeneous particle swarm optimizer (dHPSO) on dynamic unconstrained optimization problems. The results are compared to that of charged and quantum particle swarms, specifically designed for optimization in dynamic environments. It is shown that dHPSO possesses the ability to manage the diversity of the swarm dynamically, allowing it to overc... View full abstract»

• ### Adaptive Clan Particle Swarm Optimization

Publication Year: 2011, Page(s):1 - 6
Cited by:  Papers (5)
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Particle Swarm Optimization has been widely used to solve real world problems, mainly when there are too many variables to be optimized and these variables are continuous. In nature one can observe many examples of cooperative behaviors that lead to complex problem solving. Recently, some Particle Swarm Optimization variations gracefully incorporate such cooperative features with consequent benefi... View full abstract»

• ### An improved Michigan particle swarm optimization for classification

Publication Year: 2011, Page(s):1 - 7
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Classification is one of the most frequently occurring tasks of human decision making. In this paper, two improved versions of Michigan particle swarm optimization (MPSO), Improved MPSO1 (IMPSO1) and Improved MPSO2 (IMPSO2), are proposed. IMPSO1 adopts a adaptive inertia factor so as to flexibly control the search path, moreover, both nearest neighbor (NN) and 5-NN classification are used so as to... View full abstract»

• ### Magnetic particle swarm optimization

Publication Year: 2011, Page(s):1 - 7
Cited by:  Papers (1)
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In this paper, we propose a new particle swarm approach based on the idea of repulsion by a magnetic field. The structure of the method is presented and, using a number of well-known benchmark functions in a 30-dimension search space, its performance is compared to that of well-established algorithms of similar inspiration. The global search potential of the proposal is also analyzed with the aid ... View full abstract»

• ### Heterogeneous constraint handling for particle swarm optimization

Publication Year: 2011, Page(s):1 - 7
Cited by:  Papers (1)
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We propose a generic, hybrid constraint handling scheme for particle swarm optimization called Heterogeneous Constraint Handling. Inspired by the notion of social roles, we assign different constraint handling methods to the particles, one for each social role. In this paper, we investigate two social roles for particles, self' and neighbor'. Due to the usual particle dynamics, a powerful mixtur... View full abstract»

• ### A Particle Swarm Optimization approach to mixed attribute data-set classification

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (3)
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We describe a Particle Swarm Optimization (PSO) approach to the problem of classifying mixed-attribute data sets. It relies on retrieving optimal particle positions in the search space that correspond to the centroids of classes. When evaluating the fitness function, we use different mechanisms to interpret the particle positions in the description space, based on data type; as will be described, ... View full abstract»

• ### Lambda-gamma learning with feedforward neural networks using particle swarm optimization

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (2)
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The sigmoid function is a widely used, bounded activation function for feedforward neural networks (FFNNs). A problem with using bounded activation functions is that it necessitates scaling of the data to suit the fixed domain and range of the function. Alternatively the activation function itself can be adapted by learning the gradient and range of the function alongside the FFNN weights. The pur... View full abstract»

• ### An improved binary particle swarm optimization algorithm for DNA encoding enhancement

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (2)
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The accuracy of DNA computing highly depends on the DNA strands used in solving complex computations. As such, many approaches are proposed to design DNA oligonucleotides that are stable and unique. In this paper, an improved binary particle swarm optimization (IBPSO) algorithm is proposed and implemented. Four objective functions which are H-measure, similarity, hairpin and continuity are employe... View full abstract»

• ### Frontier-based multi-robot map exploration using Particle Swarm Optimization

Publication Year: 2011, Page(s):1 - 6
Cited by:  Papers (9)
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Exploring an unknown environment using team of autonomous mobile robots is an important task in many real-world applications. Many existing map exploration algorithms are based on frontier, which is the boundary between unexplored space and known open space. In the context of multiple robots, the main problem of frontier-based algorithm is to choose appropriate target points for the individual rob... View full abstract»

• ### A PSO-inspired multi-robot search algorithm independent of global information

Publication Year: 2011, Page(s):1 - 7
Cited by:  Papers (11)
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This paper presents an algorithm that coordinates mobile robots to find the desired targets without depending on precise global information. We compare the abstract solution space in PSO and physical environment that robots will explore. According to similarities and differences between them, we introduce a PSO-inspired search algorithm to guide robots to complete the search mission. Moreover, a n... View full abstract»

• ### An algorithm for self-organized aggregation of swarm robotics using timer

Publication Year: 2011, Page(s):1 - 7
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Aggregation is a basic collective behavior in biology, and is a prerequisite for many applications of swarm robotics. This paper proposes a new distributed algorithm for aggregation of swarm robotics under the constraints of no central control, no information about positions, and only local interaction among robots. Our control strategy contains two states, Search and Wait, for individual robot, a... View full abstract»

• ### Exploring different rule quality evaluation functions in ACO-based classification algorithms

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (2)
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The μAnt-Miner algorithm is an extension of the well-known Ant-Miner classification rule discovery algorithm. μAnt-Miner utilizes multiple pheromone types, one for each permitted rule class. An ant would first select the rule class and then deposit the corresponding type of pheromone. In this paper, we explore the use of different rule quality evaluation functions for rule quality as... View full abstract»

• ### A hybrid ABC-SPSO algorithm for continuous function optimization

Publication Year: 2011, Page(s):1 - 6
Cited by:  Papers (7)
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In this paper we investigate the hybridization of two swarm intelligence algorithms; namely, the Artificial Bee Colony Algorithm (ABC) and Particle Swarm Optimization (PSO). The hybridization technique is a component-based one where the PSO algorithm is augmented with an ABC component to improve the personal bests of the particles. Two different hybrid algorithms are tested in this work based on t... View full abstract»

• ### The Robot Formation Language — A formal description of formations for collective robots

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (4)
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In this paper we will present the Robot Formation Language (RFL), a topology description language for the formation of multi robot systems, such as robot swarms or self-reconfigurable modular robot platforms. The RFL supports homogeneous as well as heterogeneous multi robot platforms. This is important especially for modular robots (we also call them robot organisms), as there can also be robots i... View full abstract»

• ### Diversity control in particle swarm optimization

Publication Year: 2011, Page(s):1 - 9
Cited by:  Papers (20)
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Population diversity of particle swarm optimization (PSO) is important when measuring and dynamically adjusting algorithm's ability of “exploration” or “exploitation”. Population diversities of PSO based on L1 norm are given in this paper. Useful information on search process of an optimization algorithm could be obtained by using this measurement. Properties... View full abstract»

• ### Enhancing the food locations in an Artificial Bee Colony algorithm

Publication Year: 2011, Page(s):1 - 5
Cited by:  Papers (7)
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Artificial Bee Colony or ABC is one of the newest additions to the class of population based Nature Inspired Algorithms (NIA). In the present study we suggest some modifications in the structure of basic ABC to further improve its performance. The corresponding algorithm proposed in the present study is named Intermediate ABC (I-ABC). In I-ABC, the potential food sources are generated by using the... View full abstract»

• ### Resource allocation in bidirectional cooperative cognitive radio networks using swarm intelligence

Publication Year: 2011, Page(s):1 - 7
Cited by:  Papers (3)
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In this work we consider an OFDMA-based two-way cognitive relay network that comprises multiple source-destination pairs and multiple relays. The relays assist communication between the source-destination pairs, and different relays transmit on orthogonal subcarriers. The relays employ amplify-and-forward relaying. For this network, we formulate a sum capacity maximization problem to determine the... View full abstract»

• ### A framework for boltzmann-type models of robotic swarms

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (1)
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We introduce a new model framework to describe the temporal evolution of the macroscopic location probability of a robotic swarm in two dimensions based on the Boltzmann equation from statistical physics. The framework features a strong connection between the microscopic behavior of the robots and the macroscopic effects of this behavior. It is distinguished from other existing models by the inclu... View full abstract»

• ### A role-based imitation algorithm for the optimisation in dynamic fitness landscapes

Publication Year: 2011, Page(s):1 - 8
Cited by:  Papers (2)
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Organic Computing (OC) deals with technical systems consisting of a large number of system elements that can adapt their structure and behaviour to the operational environment in order to accomplish a given goal. In this context, self-adaptation is a key aspect that allows a system to perform in (possibly dynamic) environments without intervention from outside. Establishing self-adaptation in tech... View full abstract»

• ### Learning group behavior in games: Using Cultural Algorithms: The land bridge game engine example

Publication Year: 2011, Page(s):1 - 9
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The L-CAPS system is a functional interface for learning group behavior using Cultural Algorithms in the land bridge simulation example. It enables the Cultural Algorithms process to implicitly communicate with, modify and evaluate, autonomous game agents restricted to an external virtual world. The L-CAPS system is described and used to learn the group behavior of caribou herds in the virtual wor... View full abstract»