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» A splitting method for stochastic programs
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CCE
2004
15 years 2 months ago
Stochastic maximum principle for optimal control under uncertainty
Optimal control problems involve the difficult task of determining time-varying profiles through dynamic optimization. Such problems become even more complex in practical situatio...
Vicente Rico-Ramírez, Urmila M. Diwekar
IOR
2011
133views more  IOR 2011»
14 years 10 months ago
Finite Disjunctive Programming Characterizations for General Mixed-Integer Linear Programs
In this paper, we give a finite disjunctive programming procedure to obtain the convex hull of general mixed-integer linear programs (MILP) with bounded integer variables. We prop...
Binyuan Chen, Simge Küçükyavuz, S...
GECCO
2007
Springer
162views Optimization» more  GECCO 2007»
15 years 9 months ago
Learning noise
In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
Michael D. Schmidt, Hod Lipson
AAMAS
2010
Springer
15 years 3 months ago
Optimizing fixed-size stochastic controllers for POMDPs and decentralized POMDPs
POMDPs and their decentralized multiagent counterparts, DEC-POMDPs, offer a rich framework for sequential decision making under uncertainty. Their computational complexity, howeve...
Christopher Amato, Daniel S. Bernstein, Shlomo Zil...
GECCO
2003
Springer
117views Optimization» more  GECCO 2003»
15 years 8 months ago
A Method for Handling Numerical Attributes in GA-Based Inductive Concept Learners
This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting th...
Federico Divina, Maarten Keijzer, Elena Marchiori