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» Efficient learning algorithms for changing environments
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127
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GECCO
2007
Springer
178views Optimization» more  GECCO 2007»
15 years 10 months ago
Coevolution of intelligent agents using cartesian genetic programming
A coevolutionary competitive learning environment for two antagonistic agents is presented. The agents are controlled by a new kind of computational network based on a compartment...
Gul Muhammad Khan, Julian Francis Miller, David M....
146
Voted
NIPS
2008
15 years 5 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
176
Voted
CCGRID
2010
IEEE
15 years 1 months ago
Dynamic Load-Balanced Multicast for Data-Intensive Applications on Clouds
Data-intensive parallel applications on clouds need to deploy large data sets from the cloud's storage facility to all compute nodes as fast as possible. Many multicast algori...
Tatsuhiro Chiba, Mathijs den Burger, Thilo Kielman...
ICNS
2008
IEEE
15 years 10 months ago
Traffic Distribution Forecasting in Packet-Switching Networks
: Traffic distribution forecasting is an essential step in network planning for packet-switching networks. It is frequently necessary to forecast and develop an optimal network con...
Faramak Zandi
148
Voted
CEC
2010
IEEE
14 years 7 months ago
Co-evolutionary search path planning under constrained information-sharing for a cooperative unmanned aerial vehicle team
—Mobile cooperative sensor networks are increasingly used for surveillance and reconnaissance tasks to support domain picture compilation. However, efficient distributed informat...
Jean Berger, Jens Happe