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» Modularity for Timed and Hybrid Systems
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AAAI
2004
13 years 9 months ago
Fibring Neural Networks
Neural-symbolic systems are hybrid systems that integrate symbolic logic and neural networks. The goal of neural-symbolic integration is to benefit from the combination of feature...
Artur S. d'Avila Garcez, Dov M. Gabbay
TPDS
2010
113views more  TPDS 2010»
13 years 2 months ago
Highly Available Intrusion-Tolerant Services with Proactive-Reactive Recovery
In the past, some research has been done on how to use proactive recovery to build intrusion-tolerant replicated systems that are resilient to any number of faults, as long as reco...
Paulo Sousa, Alysson Neves Bessani, Miguel Correia...
ISDA
2008
IEEE
14 years 2 months ago
Genetic Annealing Optimization: Design and Real World Applications
Both simulated annealing (SA) and the genetic algorithms (GA) are stochastic and derivative-free optimization technique. SA operates on one solution at a time, while the GA mainta...
Mostafa A. El-Hosseini, Aboul Ella Hassanien, Ajit...
GECCO
2007
Springer
143views Optimization» more  GECCO 2007»
14 years 1 months ago
Learning and exploiting knowledge in multi-agent task allocation problems
Imagine a group of cooperating agents attempting to allocate tasks amongst themselves without knowledge of their own capabilities. Over time, they develop a belief of their own sk...
Adam Campbell, Annie S. Wu
GECCO
2006
Springer
155views Optimization» more  GECCO 2006»
13 years 11 months ago
Comparison of genetic representation schemes for scheduling soft real-time parallel applications
This paper presents a hybrid technique that combines List Scheduling (LS) with Genetic Algorithms (GA) for constructing non-preemptive schedules for soft real-time parallel applic...
Yoginder S. Dandass, Amit C. Bugde