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» Evolving Neural Network through Augmenting Topologies
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GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
15 years 2 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
IEEEPACT
2008
IEEE
15 years 4 months ago
Feature selection and policy optimization for distributed instruction placement using reinforcement learning
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
Katherine E. Coons, Behnam Robatmili, Matthew E. T...
ATC
2010
Springer
14 years 8 months ago
Agent-Augmented Co-Space: Toward Merging of Real World and Cyberspace
Co-Space refers to interactive virtual environment modelled after the real world we are situated in. Through realistic 3D modelling and animation technologies, Co-Space simulates t...
Ah-Hwee Tan, Yilin Kang
SIGCOMM
2010
ACM
14 years 9 months ago
c-Through: part-time optics in data centers
Data-intensive applications that operate on large volumes of data have motivated a fresh look at the design of data center networks. The first wave of proposals focused on designi...
Guohui Wang, David G. Andersen, Michael Kaminsky, ...
FUIN
2008
103views more  FUIN 2008»
14 years 9 months ago
Implementing Sorting Networks with Spiking Neural P Systems
Spiking neural P systems simulate the behavior of neurons sending signals through axons. Recently, some applications concerning Boolean circuits and sorting algorithms have been pr...
Rodica Ceterchi, Alexandru Ioan Tomescu