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» Complex networks as control paradigm for complex systems
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CEC
2009
IEEE
16 years 1 months ago
Lamarckian neuroevolution for visual control in the Quake II environment
Abstract— A combination of backpropagation and neuroevolution is used to train a neural network visual controller for agents in the Quake II environment. The agents must learn to...
Matt Parker, Bobby D. Bryant
AI
2007
Springer
16 years 19 days ago
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Changhe Yuan, Marek J. Druzdzel
GPC
2007
Springer
16 years 18 days ago
Heterogeneous Wireless Sensor Network Deployment and Topology Control Based on Irregular Sensor Model
Heterogeneous wireless sensor network (heterogeneous WSN) consists of sensor nodes with different ability, such as different computing power and sensing range. Compared with homoge...
Chun-Hsien Wu, Yeh-Ching Chung
FTDCS
2004
IEEE
15 years 10 months ago
Self-Aware Distributed Embedded Systems
Distributed embedded sensor networks are now being successfully deployed in environmental monitoring of natural phenomena as well as for applications in commerce and physical secu...
Richard Pon, Maxim A. Batalin, Mohammad H. Rahimi,...
KES
2005
Springer
15 years 12 months ago
Recognizing and Simulating Sketched Logic Circuits
This paper presents a system for recognizing sketched logic circuits in real-time and graphically simulating them afterwords. It has been developed for use in university and school...
Marcus Liwicki, Lars Knipping