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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Reynolds, Robert G. Kinnaird-Heether, Leonard Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9781538627266

cultural algorithms provide a meta-heuristic framework for the application of various solution mechanism represented by Knowledge Sources in the Belief Space to the evolution of complex social networks in the population space. One of the key components in the configuration of a cultural Algorithm is the knowledge distribution mechanism, the means with which the influence of a solution approach is spread out among individuals in individual subnetworks. In this paper a new method of Knowledge distribution called the population mechanism is introduced and its performance compared in complex real-valued functional landscapes. While capable of generating solutions to the entire range of problem, from fixed to chaotic, they are best utilized for fixed problems containing of low to high variability but begin to lose their edge with increasing periodicity. It is proposed that the population mechanism when paired with other previous forms of knowledge distribution will be able to provide focus in specific areas of search and provide a framework with which to provide metrics to build a cultural Engine.

关键词： cultural algorithms Metaheuristics population mechanism evolutionary computation problem complexity social networks optimization problem solving

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Problem Solving Using Social Networks in cultural algorithms with Auctions

Problem Solving Using Social Networks in Cultural Algorithms...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Reynolds, Robert G. Kinnaird-Heether, Leonard Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9781509046010

cultural algorithms provide a meta-heuristic framework for the application of various solution mechanism represented by Knowledge Sources in the Belief Space to the evolution of complex social networks in the population space. One of the key components in the configuration of a cultural Algorithm is the knowledge distribution mechanism, how the influence of a solution approach is spread out among individuals in individual subnetworks. In this paper a specific set of Knowledge distribution mechanisms based upon various Auction models are introduced and their performance compared in complex real-valued functional landscapes. While capable of generating solutions to the entire range of problem, from fixed to chaotic, they are best utilized for fixed problems containing of low to high variability but begin to lose their edge with increasing periodicity. It is proposed that auction mechanisms will be most likely found in subcultures where problems associated with that culture have reasonably strong signals that can afford the opportunity to make quick and precise decisions.

关键词： cultural algorithms Metaheuristics auction mechanisms evolutionary computation problem complexity social networks and optimization problem solving

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Medical image restoration approach using cultural algorithms

Medical image restoration approach using cultural algorithms

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Conference on Medical Imaging, Parallel Processing of Images, and Optimization Techniques

作者： Pan, Zhongliang Chen, Ling S China Normal Univ Sch Phys & Telecommun Engn Guangzhou 510006 Guangdong Peoples R China

ISBN: (纸本)9780819469533

In medical image processing, the image degradation often occurs. The image restoration is to recover the original image from its noisy and blurred version. A restoration approach using cultural algorithms for medical images is presented in this paper. First of all, the representation of image degradation model is built. Secondly, an image is encoded as an individual;the fitness of an individual is defined. An algorithm based on the principle of cultural algorithms is presented for obtaining the ideal images from the blurred image. The algorithm consists of the population space, the belief space, and the communication protocol that describes the exchange mode of knowledge between the population space and belief space. A few type of knowledge, such as the situational knowledge and the normative knowledge etc., are used. The images with better quality are obtained by the evolution of populations. The experimental results show that the image restoration approach proposed in this paper can obtain the good approximations of the original image.

关键词： medical image image restoration image degradation cultural algorithms evolutionary algorithms

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GPU-Accelerated Standard and Multi-Population cultural algorithms

GPU-Accelerated Standard and Multi-Population Cultural Algor...

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International Conference on Service Science (ICSS)

作者： Dong, Jianqiang Yuan, Bo Tsinghua Univ Grad Sch Shenzhen Intelligent Comp Lab Div Informat Shenzhen 518055 Peoples R China

ISBN: (纸本)9780769549729

In this paper, we present three parallel cultural algorithms using CUDA-enabled GPUs. Firstly, we used the GPU to accelerate an expensive fitness function. Next, the parallel versions of both standard and multi-population CAs were presented. Experiments show that the standard CA with an expensive fitness function was made more than 600 times faster. On lightweight benchmark problems, the speedups were only 3-4 times for the standard CA while the multi-population CA can still achieve 30-50 times speedups.

关键词： GPU CUDA acceleration cultural algorithms multi-population clustering

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Using cultural algorithms to Learn the Impact of Climate on Local Fishing Behavior in Cerro Azul, Peru

Using Cultural Algorithms to Learn the Impact of Climate on ...

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IEEE Congress on Evolutionary Computation (CEC) as part of the IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Kattan, Khalid A. Reynolds, Robert G. Wayne State Univ Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9781728169293

Recently it has been found that the earth's oceans are warming at a pace that is 40% faster than predicted by a United Nations panel a few years ago. As a result, 2018 has become the warmest year on record for the earth's oceans. That is because the oceans have acted as a buffer by absorbing 93% of the heat produced by the greenhouse gases [1]. The impact of the oceanic warming has already been felt in terms of the periodic warming of the Pacific Ocean as an effect of the ENSO process. The ENSO process is a cycle of warming and subsequent cooling of the Pacific Ocean that can last over a period of years. This cycle was first documented by Peruvian fishermen in the early 1600's. So it has been part of the environmental challenges that have been presented to economic agents throughout the world since then. It has even been suggested that the cycle has increased in frequency over the years, perhaps in response to the overall issues related to global warming. [2] [3] In this paper cultural algorithms are used to develop a multi-objective agent-based model of artisanal (traditional offshore) fishing behavior in coastal Peru, Cerro Azul. The data used to produce this model comes from the observation of fishing behavior over a four year period, 1982-1986. During this period over 6000 individual fishing trips were documented. This observation period overlapped with one of the largest ENSO activities ever recorded. As a result, it was possible to observe the changes in fishing behavior that were the result of this process. While the data is several decades old, the ENSO process was first observed in Peru in 1502. Thus, this data can be considered to reflect the adaptations that have been made to the process in the ensuing centuries. The model was used to produce Pareto curves that reflected tradeoffs in terms of fish quality and trip effort during each of three phases on the ENSO process. A version of cultural algorithms, CAPSO, was then used to compute whether these curves

关键词： cultural algorithms cultural Engine Model Multi-objective optimization Pareto Optimality Climate Change

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Using cultural algorithms to Improve Intelligent Logistics

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5th International Conference on Hybrid Artificial Intelligence Systems

作者： Ochoa, Alberto Garcia, Yazmani Yanez, Javier Teymanoglu, Yaddik Juarez City Univ Juarez City Mexico CIATEC Mexico City DF 37545 Mexico Edirne Univ Edirne Turkey

ISBN: (纸本)9783642138027

Today the issue of logistics is a very important within companies to the extent that some have departments devoted exclusively to it. This has evolved over time and today is a fundamental aspect in the fight business seeking to consolidate or remain leaders in their field. With the above we know that logistics can be divided into different classes, however, in this regard, our study is based on the timely distribution to the customer with a lower cost, higher sales and better utilization of space resulting in excellent service. Finally, prepare a comparative analysis of the results with respect to another method of optimization solution space.

关键词： Logistics Data Mining cultural algorithms Population Space Space of Beliefs Protocol Bin Packing Simplex Method

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cultural algorithms, an alternative heuristic to solve the job shop scheduling problem

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ENGINEERING OPTIMIZATION 2007年第1期39卷 69-85页

作者： Rivera, Daniel Cortes Becerra, Ricardo Landa Coello, Carlos A. Coello CINVESTAV IPN Evolutionary Computat Grp Dept Ingn ElectrSecc Computac Mexico City 07300 DF Mexico

In this work, an approach for solving the job shop scheduling problem using a cultural algorithm is proposed. cultural algorithms are evolutionary computation methods that extract domain knowledge during the evolutionary process. Additional to this extracted knowledge, the proposed approach also uses domain knowledge given a priori (based on specific domain knowledge available for the job shop scheduling problem). The proposed approach is compared with respect to a Greedy Randomized Adaptive Search Procedure (GRASP), a Parallel GRASP, a Genetic Algorithm, a Hybrid Genetic Algorithm, and a deterministic method called shifting bottleneck. The cultural algorithm proposed in this article is able to produce competitive results with respect to the two approaches previously indicated at a significantly lower computational cost than at least one of them and without using any sort of parallel processing.

关键词： cultural algorithms evolutionary algorithms evolutionary programming job shop scheduling metaheuristics

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Learning the Impact of Group Structure on Optimal Herd Path Planning with cultural algorithms

Learning the Impact of Group Structure on Optimal Herd Path ...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Palazzolo, Thomas Zhang, Chencheng Saad, Sarah Reynolds, Robert G. Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Univ Michigan Museum Anthropol Archaeol Ann Arbor MI 48109 USA

ISBN: (数字)9781665467087

ISBN: (纸本)9781665467087

This paper compares several approaches to cooperative multi-agent path planning (MAP) based upon variations of the A* algorithm. To simulate multi-agent migration patterns three path-finding mechanisms based on the classic A* algorithm was utilized: A*;A*, Ambush and Dendriform. Each makes different assumptions about group leadership in terms of their path generation. A* assumes a single leader for the migratory group: A*mbush allows the group to move in waves;and Dendriform allows the group to decompose and recompose into groups of arbitrary size with local leaders. Each mechanism required parameter weightings so that the simulated agents would interact realistically with their environment. cultural algorithms were employed to adjust the parameter weight categories in order to optimize the group movement under each of these leadership strategies. The three approaches were applied to the simulation of a real-world multi-agent system, the migration of large herd of caribou. The simulated migration was part of the Deepdive Virtual Reality system. In those simulations A* with a single planning agent emphasized nutrition at the expense of the other parameters. A*mbush learned to reduce nutrition slightly and while increasing its emphasis on risk and exploration. On the other hand, Dendriform emphasized overall effort since its planning more dynamic and required more concentration on local effort to be optimized.

关键词： cultural algorithms Evolutionary Learning Swarm Intelligence Virtual Reality Cooperative Multi-Agent Path Planning

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Exploring Ancient Landscapes Under Lake Huron Using cultural algorithms

Exploring Ancient Landscapes Under Lake Huron Using Cultural...

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Conference of the Complex Adaptive Systems on Responding to Continuous Global Change in Systems Needs

作者： Vitale, Kevin Reynolds, Robert O'Shea, John Meadows, Guy Wayne State Univ 5057 Woodward Detroit MI 48202 USA Univ Michigan Ann Arbor MI 48109 USA

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 world. (C) 2011 Published by Elsevier B. V.

关键词： cultural algorithms Serious Games Multi-agent Simulation Crowd Behavior

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Threshold segmentation using cultural algorithms for image analysis

Threshold segmentation using cultural algorithms for image a...

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International Conference on Photoelectronic Detection and Imaging

作者： Pan Zhongliang Chen Ling Zhang Guangzhao S China Normal Univ Sch Phys & Telecommun engn Guangzhou 510006 Guangdong Peoples R China Sun Yat Sen Univ Dept Elect Commun Guangzhou 510275 Guangdong Peoples R China

ISBN: (纸本)9780819467676

The image segmentation is often an important step in the analysis of images. In this paper, an image segmentation method based on cultural algorithms is presented. The method performs the image segmentation by selecting the optimal threshold values. The multi-threshold values are used. First of all, an entropy function corresponding to an image is defined. The optimal threshold values are obtained by making the entropy function reach the maximal value. Secondly, an algorithm based on the principle of cultural algorithms is presented for the computation of the optimal thresholds. The algorithm consists of three major components: a population space, a belief space, and a communication protocol that describes how knowledge is exchanged between the first two components. The designs and implementations of the three components are given in detail. The experimental results show that the segmentation method proposed in this paper can obtain the near optimal threshold for image segmentation.

关键词： image segmentation threshold segmentation cultural algorithms evolutionary algorithms.

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