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Engineering cooperative smart things based on embodied cognition

Nathalia Moraes do Nascimento, Carlos Jose Pereira de Lucena
2017 2017 NASA/ESA Conference on Adaptive Hardware and Systems (AHS)  
The behavior of these embodied agents is autonomously configured through an evolutionary algorithm that is triggered according to the application performance.  ...  In order to achieve the goal of a smart IoT application, such as minimizing waste transportation costs or reducing energy consumption, the smart things in the application scenario must cooperate with each  ...  Our thanks to CNPq, CAPES, FAPERJ and PUC-Rio for their support through scholarships and fellowships.  ... 
doi:10.1109/ahs.2017.8046366 dblp:conf/ahs/NascimentoL17 fatcat:yeyirznv5jgfddgjkzu7i2ggjq

Theory and applications of neural maps

Thomas Villmann, Udo Seiffert, Axel Wismüller
2004 The European Symposium on Artificial Neural Networks  
Therby we concentrate on two well-known examples: Self-Organizing Maps and Neural Gas. Moreover we briefly reflect outstanding applications showing the power of neural maps.  ...  In this tutorial paper about neural maps we review the current state in theoretical aspects like mathematical treatment of convergence, ordering and topography, magnification and others.  ...  Vice versa, neighborhood cooperativeness known from neural maps are incorporated in strategies in evolutionary approaches, too.  ... 
dblp:conf/esann/VillmannSW04 fatcat:z35oqpqzxfc3bcwueomir7lk5y

Intelligent Systems: Architectures and Perspectives [chapter]

Ajith Abraham
2003 Studies in Fuzziness and Soft Computing  
An important advantage of probabilistic reasoning is its ability to update previous outcome estimates by conditioning them with newly available evidence [57].  ...  free optimization techniques such as Evolutionary Computation (EC).  ...  Acknowledgements Author is grateful to Professor Lakhmi Jain (University of South Australia, Adelaide) and the three referees for the technical comments, which improved the clarity of this chapter.  ... 
doi:10.1007/978-3-7908-1770-6_1 fatcat:u7g7qckslzcyxnxghenpzuwpma

Neural Network Radial Basis Function classifier for earthquake data using aFOA

Anurag Rana, Arjun Kumar, Ankur Sharma
2016 International Journal of Advanced Research  
This research was limned the motivation for using Artificial Neural Networks with the assistance of evolutionary swarm algorithm such as fruit fly optimization algorithm to be competent tool in finding  ...  Step 7 Crossovers: In global cooperation search each flies in the poor half crossover it with the corresponding one.  ... 
doi:10.21474/ijar01/1244 fatcat:gjctq4mktnbq3hnvyyugctjhqq

Self-Organizing Potential Field Network: A New Optimization Algorithm

Lu Xu, Tommy Wai Shing Shing
2010 IEEE Transactions on Neural Networks  
Index Terms-Neural network, self-organizing map, stochastic optimization, vector potential field.  ...  The results presented illustrate that the SOPFN algorithm achieves a significant performance improvement on multimodal problems compared with other evolutionary optimization algorithms.  ...  Acknowledgment The authors would like to thank the editors and anonymous reviewers for providing valuable comments and suggestions.  ... 
doi:10.1109/tnn.2010.2047264 pmid:20570771 fatcat:t3vcpbe465elzbrcdpjp7y4fea

Adaptation of Fuzzy Inference System Using Neural Learning [chapter]

A. Abraham
2005 Studies in Fuzziness and Soft Computing  
The integration of neural networks and fuzzy inference systems could be formulated into three main categories: cooperative, concurrent and integrated neuro-fuzzy models.  ...  We present three different types of cooperative neurofuzzy models namely fuzzy associative memories, fuzzy rule extraction using self-organizing maps and systems capable of learning fuzzy set parameters  ...  Fortunately, evolutionary algorithms work with a population of independent solutions, which makes it easy to distribute the computational load among several processors using parallel algorithms.  ... 
doi:10.1007/11339366_3 fatcat:hyt6m7zr3bfnxjv24bxrwkz6la

Artificial Intelligence in the Path Planning Optimization of Mobile Agent Navigation

Sándor T. Brassai, Barna Iantovics, Călin Enăchescu
2012 Procedia Economics and Finance  
One of the major directions in artificial intelligence consists in the development of efficient computational intelligence algorithms, like: evolutionary algorithms, and neural networks.  ...  Systems, that operate in isolation or cooperate with each other, like mobile robots could use computational intelligence algorithms for different problems/tasks solving, however in their behavior could  ...  The Kohonen map is an artificial neural network with an unsupervised training algorithm Kohonen, 2011.  ... 
doi:10.1016/s2212-5671(12)00147-5 fatcat:vl5o654nvnbsbnxy5gxy7sw2ee

An efficient self-organizing map designed by genetic algorithms for the traveling salesman problem

Hui-Dong Jin, Kwong-Sak Leung, Man-Leung Wong, Zong-Ben Xu
2003 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
Index Terms-Convex hull, genetic algorithms, neural-evolutionary system, neural networks, self-organizing map, traveling salesman problem.  ...  In this paper, we develop a self-organizing map (SOM) with a novel learning rule.  ...  ACKNOWLEDGMENT The authors would like to thank the anonymous referees for their careful reading of this paper and for their valuable and constructive comments, which have helped to improve the quality  ... 
doi:10.1109/tsmcb.2002.804367 pmid:18238240 fatcat:aedv7ar63vexfh6ahvsfgwkj2a

Behavioral Diversity, Choices and Noise in the Iterated Prisoner's Dilemma

S.Y. Chong, X. Yao
2005 IEEE Transactions on Evolutionary Computation  
Fink Prize Paper Award for his work on evolutionary artificial neural networks. He is the Editor-in-Chief of the IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION.  ...  time complexity of evolutionary algorithms, coevolution, iterated prisoner's dilemma, data mining, and real-world applications.  ...  The authors are grateful to Dr. D. B. Fogel and four anonymous reviewers for their constructive comments that have helped greatly in improving this paper.  ... 
doi:10.1109/tevc.2005.856200 fatcat:clrb3t3c7jdnlkqwj6mbityfiq

Self-Organizing and Self-Evolving Neurons: A New Neural Network for Optimization

Sitao Wu, Tommy W. S. Chow
2007 IEEE Transactions on Neural Networks  
A self-organizing and self-evolving agents (SOSENs) neural network is proposed. Each neuron of the SOSENs evolves itself with a simulated annealing (SA) algorithm.  ...  Every neuron exhibits a self-organizing behavior, which is similar to those of the self-organizing map (SOM), particle swarm optimization (PSO), and self-organizing migrating algorithm (SOMA).  ...  ACKNOWLEDGMENT The authors would like to thank the anonymous reviewers' useful suggestions that greatly improved the format of this paper.  ... 
doi:10.1109/tnn.2006.887556 pmid:17385627 fatcat:gdmalk6bqfe5vk7vhw4kmtfmdi

Attention mechanism and its role in invariant pattern recognition

Xiaodong Zeng
2001 Neurocomputing  
A neural network model based on this concept is tested.  ...  The local mappings m ?@ describe the mapping from the neighborhood of grid a onto the neighborhood of grid b. The weight functions w ?  ...  A practicable solution is to use a combination of both algorithms according to the state of the matching. We choose the order of links as the state parameter s" ?@ (w ?@ N ?  ... 
doi:10.1016/s0925-2312(01)00514-8 fatcat:d552itcvsba2rgrwulh5qbfdyq

Multi-scale metrics and self-organizing maps: a computational approach to the structure of sensory maps [article]

William H. Wilson
2018 arXiv   pre-print
This paper introduces the concept of a bi-scale metric for use in the cooperative phase of the self-organizing map (SOM) algorithm.  ...  When a bi-scale metric is appropriately applied, issues with map neurons that are not activated by any point in the training data are reduced or eliminated.  ...  neural maps and the SOM algorithm.  ... 
arXiv:1805.03337v1 fatcat:c43mjhdgvzdjxj52y3w53d5ssi

Multistrategy Self-Organizing Map Learning for Classification Problems

S. Hasan, S. M. Shamsuddin
2011 Computational Intelligence and Neuroscience  
Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics.  ...  The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test.  ...  Acknowledgments Authors would like to thank the Research Management Centre (RMC), Universiti Teknologi Malaysia, and the Soft Computing Research Group (SCRG) for the support in making this studies a success  ... 
doi:10.1155/2011/121787 pmid:21876686 pmcid:PMC3157650 fatcat:lca3yecmobdapgbriilok3pgja

Cooperative, hybrid agent architecture for real-time traffic signal control

Min Chee Choy, D. Srinivasan, Ruey Long Cheu
2003 IEEE transactions on systems, man and cybernetics. Part A. Systems and humans  
learning, learning rate and weight adjustment as well as dynamic update of fuzzy relations using evolutionary algorithm.  ...  The large-scale traffic signal control problem is divided into various subproblems, and each subproblem is handled by an intelligent agent with fuzzy neural decision-making module.  ...  ACKNOWLEDGMENT The authors would like to thank the Land Transportation Authority of Singapore (LTA) for providing data necessary for the simulation modeling and F. Logi for his advice.  ... 
doi:10.1109/tsmca.2003.817394 fatcat:i7zeyho2gncrfddt5i534uheke

Engineering Evolutionary Intelligent Systems: Methodologies, Architectures and Reviews [chapter]

Ajith Abraham, Crina Grosan
2008 Studies in Computational Intelligence  
Designing intelligent paradigms using evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision,  ...  In this Chapter, we illustrate the various possibilities for designing intelligent systems using evolutionary algorithms and also present some of the generic evolutionary design architectures that has  ...  Evolutionary algorithms are used to adapt the connection weights, network architecture and learning rules according to the problem environment.  ... 
doi:10.1007/978-3-540-75396-4_1 fatcat:xplkbxzk4vbpbmnp4zxrjomj3q
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