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TEC
2002
163views more  TEC 2002»
13 years 7 months ago
Ants can solve constraint satisfaction problems
In this paper, we describe a new incomplete approach for solving constraint satisfaction problems (CSPs) based on the ant colony optimization (ACO) metaheuristic. The idea is to us...
Christine Solnon
IWQOS
2004
Springer
14 years 25 days ago
Topology design for service overlay networks with bandwidth guarantees
— The Internet still lacks adequate support for QoS applications with real-time requirements. In great part, this is due to the fact that provisioning of end-to-end QoS to traf...
S. L. Vieira, Jörg Liebeherr
COR
2007
134views more  COR 2007»
13 years 7 months ago
Portfolio selection using neural networks
In this paper we apply a heuristic method based on artificial neural networks (NN) in order to trace out the efficient frontier associated to the portfolio selection problem. We...
Alberto Fernández, Sergio Gómez
AAAI
1994
13 years 8 months ago
Solution Reuse in Dynamic Constraint Satisfaction Problems
Many AI problems can be modeled as constraint satisfaction problems (CSP), but many of them are actually dynamic: the set of constraints to consider evolves because of the environ...
Gérard Verfaillie, Thomas Schiex
AAAI
2007
13 years 9 months ago
Learning to Solve QBF
We present a novel approach to solving Quantified Boolean Formulas (QBF) that combines a search-based QBF solver with machine learning techniques. We show how classification met...
Horst Samulowitz, Roland Memisevic