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COR
2007
133views more  COR 2007»
15 years 2 months ago
Reverse logistics network design with stochastic lead times
This work is concerned with the efficient design of a reverse logistics network using an extended version of models currently found in the literature. Those traditional, basic mo...
Kris Lieckens, Nico Vandaele
ICML
2005
IEEE
16 years 3 months ago
Bounded real-time dynamic programming: RTDP with monotone upper bounds and performance guarantees
MDPs are an attractive formalization for planning, but realistic problems often have intractably large state spaces. When we only need a partial policy to get from a fixed start s...
H. Brendan McMahan, Maxim Likhachev, Geoffrey J. G...
120
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ICML
1995
IEEE
16 years 3 months ago
Stable Function Approximation in Dynamic Programming
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
Geoffrey J. Gordon
SIGDIAL
2010
15 years 11 days ago
Sparse Approximate Dynamic Programming for Dialog Management
Spoken dialogue management strategy optimization by means of Reinforcement Learning (RL) is now part of the state of the art. Yet, there is still a clear mismatch between the comp...
Senthilkumar Chandramohan, Matthieu Geist, Olivier...
CDC
2009
IEEE
143views Control Systems» more  CDC 2009»
15 years 5 months ago
Parameter approximate dynamic optimization for PSO systems
— This paper presents a novel swarm approximate dynamic programming method (swarm-ADP) for parameter optimization of PSO systems, from the perspective of optimal control. Based o...
Qi Kang, Lei Wang, Derong Liu, Qidi Wu