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Guest editorial: special issue on parallel and distributed evolutionary algorithms, part two

Marco Tomassini, Leonardo Vanneschi
2010 Genetic Programming and Evolvable Machines  
Welcome to part 2 of the two-part special issue on parallel and distributed Evolutionary Algorithms (EAs).  ...  As already pointed out in the editorial of part 1 [1], despite the long history of parallel and distributed approaches in EAs, still a lot of motivations exist for a new presentation of the state of the  ...  The second paper, by Wilson and Banzhaf, is another example of the present trend in GP towards the use of powerful and inexpensive GPUs for data-intensive parallel processing.  ... 
doi:10.1007/s10710-010-9106-1 fatcat:fm7rqpb77vhcbo77ua6nnb4oye

Introduction: special issue on parallel and distributed evolutionary algorithms, part I

Marco Tomassini, Leonardo Vanneschi
2009 Genetic Programming and Evolvable Machines  
Parallel and distributed approaches are natural in evolutionary computation and they have been used intensively since the early years of this research field.  ...  Evolutionary algorithms, in fact, have often been described as intrinsically parallel computational methods.  ...  The present special issue was conceived for presenting high quality work on parallel and distributed approaches in evolutionary computation, targeting a wide set of researchers ranging from specialists  ... 
doi:10.1007/s10710-009-9094-1 fatcat:fkgnzvexcjeyvdflbrtckussxi

Research Status and Development Trend of Bioheuristic Computing

zhijun Chai, Zhao Li
2019 IOP Conference Series: Materials Science and Engineering  
A few future directions and research challenges are presented, such as parallel bio-in-spired computation, bio-inspired computation with reasoning and knowledge, bio-inspired dynamics computation, bio-inspired  ...  model and computing method, so as to serve the scientific research and engineering application of human society.  ...  parameters adaptive adjusting mechanism, the evolutionary computation fitness evaluation mechanism, the evolutionary computation fault-tolerant mechanism and parallel evolutionary computation, etc.  ... 
doi:10.1088/1757-899x/646/1/012040 fatcat:kifjbw7ou5acpm4weph564cbji

The morphological state space revisited: what do phylogenetic patterns in homoplasy tell us about the number of possible character states?

Jennifer F. Hoyal Cuthill
2015 Interface Focus  
Yet the evolution of new states along a lineage is a general prediction of evolutionary trends [4] .  ...  search for evolutionary trends.  ... 
doi:10.1098/rsfs.2015.0049 pmid:26640650 pmcid:PMC4633860 fatcat:6kvstk3gp5gqdekbsdtl65yjmm

A Review on Data mining from Past to the Future

Venkatadri. M, Lokanatha C. Reddy
2011 International Journal of Computer Applications  
Hence, this paper discusses the various improvements in the field of data mining from past to the present and explores the future trends.  ...  Advancements in Statistics, Machine Learning, Artificial Intelligence, Pattern Recognition and Computation capabilities have evolved the present day's data mining applications and these applications have  ...  Computing Resources The contemporary developments in high speed connectivity, parallel, distributed, grid and cloud computing has posed new challenges for data mining.  ... 
doi:10.5120/1961-2623 fatcat:6w4qyny3ibcuvp732x47f2f344

IEEE Access Special Section Editorial: Artificial Intelligence in Parallel and Distributed Computing

Songwne Pei, Junjie Wu, Tao Li, Yong Chen, Stephane Zuckerman
2021 IEEE Access  
, parallel computing methodologies, distributed computing models, new computer architectures, cloud computing, data centers, and so on.  ...  Traditional computation is driven by parallel accelerators or distributed computation nodes in order to improve computing performance, save energy, and decrease delays in accessing memory.  ... 
doi:10.1109/access.2020.3048598 fatcat:dfj2ja4glzhyphng56fkrahtxq

StreamGP

Gianluigi Folino, Clara Pizzuti, Giandomenico Spezzano
2007 Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07  
Only in such a case the algorithm is executed to generate a new set of classifiers to update the current ensemble.  ...  Experimental results on a synthetic and real life data set showed the validity of the approach in maintaining an accurate and up-to-date GP ensemble.  ...  ACM 978-1-59593-697-4/07/0007. dictors in the form of cooperative subpopulations and exploits the inherent parallelism of GP by sharing the computational workload among computers over the network.  ... 
doi:10.1145/1276958.1277301 dblp:conf/gecco/FolinoPS07 fatcat:kzhgwr2mczfdpcfrsrn3bi5qqy

Genetic Programming in Wireless Sensor Networks [chapter]

Derek M. Johnson, Ankur M. Teredesai, Robert T. Saltarelli
2005 Lecture Notes in Computer Science  
New techniques for evolutionary computing (EC) are needed to address these new computing models.  ...  In this paper we first discuss an evolutionary computing algorithm that operates within a distributed wireless sensor network. Such algorithms include continuous evolutionary computing.  ...  Such current trends in paintable or spray computing are summarized by Mamei [4] .  ... 
doi:10.1007/978-3-540-31989-4_9 fatcat:tdse2733efeh7h36lp5qsdqrcu

RPL2: A language and parallel framework for evolutionary computing [chapter]

Patrick D. Surry, Nicholas J. Radcliffe
1994 Lecture Notes in Computer Science  
The Reproductive Plan Language 2 (RPL2) is an extensible interpreted language for writing and using evolutionary computing programs.  ...  It supports arbitrary genetic representations, all structured population models described in the literature together with further hybrids, and runs on parallel or serial hardware while hiding parallelism  ...  The parallel prototype was developed by Graham Jones (1992) . Mark Green and Ian Boyd from British Gas worked together with Patrick Surry on the design and implementation of RPL2.  ... 
doi:10.1007/3-540-58484-6_305 fatcat:qf4hqoealnglxbmx7hiixn6lsq

2015 Index IEEE Computational Intelligence Magazine Vol. 10 [Year-End Index]

2015 IEEE Computational Intelligence Magazine  
., +, MCI Aug. 2015 8 New Trends of Learning in Computational Intelligence [Guest Editorial].  ...  ., +, MCI Aug. 2015 42-51 New Trends of Learning in Computational Intelligence [Guest Editorial].  ... 
doi:10.1109/mci.2015.2492758 fatcat:pxnvbhqt6jdcpjhstbh32qysfm

A note on new trends in data-aware scheduling and resource provisioning in modern HPC systems

Jie Tao, Joanna Kolodziej, Rajiv Ranjan, Prem Prakash Jayaraman, Rajkumar Buyya
2015 Future generations computer systems  
The paper ''Artificial Neural Network Support to Monitoring of the Evolutionary Driven Security Aware Scheduling in Computational Distributed Environments'' [5] proposes an artificial neural network  ...  The paper ''Resource-Aware Hybrid Scheduling Algorithm in Heterogeneous Distributed Computing'' [4] presents a novel scheduling technique for tasks over distributed computing architectures.  ... 
doi:10.1016/j.future.2015.04.016 fatcat:z2254f74bjdhtgoxus44ogqkyq

Distributed Parametric Optimization with the Geneva Library [chapter]

Rudiger Berlich, Sven Gabriel, Ariel Garcia, Marcel Kunze
2011 Data Driven e-Science  
: • New trend to do distributed computation (not the least due to Linux !!)  ...   Geneva (read "Grid-enabled evolutionary algorithms") is a C++ library of optimization algorithms targetted at large scale problems • Designed with parallelism in mind • Allows multi-threaded or distributed  ... 
doi:10.1007/978-1-4419-8014-4_24 fatcat:auekcqkwbjca5prafm7rfw3wrq

2019 Index IEEE Transactions on Emerging Topics in Computational Intelligence Vol. 3

2019 IEEE Transactions on Emerging Topics in Computational Intelligence  
., +, TETCI June 2019 271-285 Evolutionary computation A Novel Portfolio Optimization Model Based on Trend Ratio and Evolutionary Computation.  ...  Guest Editorial: Special Issue on New Advances in Deep-Transfer Learning. Deng, Z., +, TETCI Oct. 2019 357-359 Guest Editorial: Special Issue on New Trends in Smart Chips and Smart Hardware.  ...  Goods distribution New  ... 
doi:10.1109/tetci.2019.2960994 fatcat:2crjc5ajvzdxpj3g6nqmgkimpm

Evolutionary Robotics: A Review

Horatiu Voicu
2002 The AI Magazine  
Currently, many details of the natural evolutionary process are ignored in their artificial counterpart because of computational limitations.  ...  He received an M.S. in computer science from the Technical University of Iasi, Romania, in 1996.  ...  Distributed knowledge discovery (DKD) works with the merger of communication and computation by analyzing data in a distributed fashion.  ... 
doi:10.1609/aimag.v23i2.1648 dblp:journals/aim/Voicu02 fatcat:ta3kw3o3w5cdxmrxi223ceuyki

A Parallel evolutionary approach to multi-objective optimization

Xiang Feng, Francis C.M. Lau
2007 2007 IEEE Congress on Evolutionary Computation  
This paper proposes a new approach based on the generic generalized particle model (GE-GPM) for computing in parallel approximate efficient solutions for the distribution problem with multiple objectives  ...  Evolutionary algorithms have been used since the mid-eighties to solve complex single and multi-objective optimization problems.  ...  The evolutionary experimental results and the optimization trend from t = 0 to t = 18 are shown in Fig. 4 and Fig. 5 .  ... 
doi:10.1109/cec.2007.4424606 dblp:conf/cec/FengL07 fatcat:4zqp5k3ckjccpfncl4fwsza3sm
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