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» A splitting method for stochastic programs
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CCE
2004
13 years 7 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»
13 years 2 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»
14 years 1 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
13 years 7 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»
14 years 23 days 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