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» Solving Hierarchical Optimization Problems Using MOEAs
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ICML
2004
IEEE
16 years 1 months ago
Learning to fly by combining reinforcement learning with behavioural cloning
Reinforcement learning deals with learning optimal or near optimal policies while interacting with the environment. Application domains with many continuous variables are difficul...
Eduardo F. Morales, Claude Sammut
WLP
2005
Springer
15 years 6 months ago
Expressing Interaction in Combinatorial Auction through Social Integrity Constraints
Abstract. Combinatorial Auctions are an attractive application of intelligent agents; their applications are countless and are shown to provide good revenues. On the other hand, on...
Marco Alberti, Federico Chesani, Alessio Guerri, M...
TCAD
2008
136views more  TCAD 2008»
15 years 12 days ago
A Geometric Programming-Based Worst Case Gate Sizing Method Incorporating Spatial Correlation
We present an efficient optimization scheme for gate sizing in the presence of process variations. Our method is a worst-case design scheme, but it reduces the pessimism involved i...
Jaskirat Singh, Zhi-Quan Luo, Sachin S. Sapatnekar
ASPDAC
2000
ACM
154views Hardware» more  ASPDAC 2000»
15 years 4 months ago
Dynamic weighting Monte Carlo for constrained floorplan designs in mixed signal application
Simulated annealing has been one of the most popular stochastic optimization methods used in the VLSI CAD field in the past two decades for handling NP-hard optimization problems...
Jason Cong, Tianming Kong, Faming Liang, Jun S. Li...
TEC
2010
173views more  TEC 2010»
14 years 7 months ago
Analysis of Computational Time of Simple Estimation of Distribution Algorithms
Estimation of distribution algorithms (EDAs) are widely used in stochastic optimization. Impressive experimental results have been reported in the literature. However, little work ...
Tianshi Chen, Ke Tang, Guoliang Chen, Xin Yao