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151views
14 years 5 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis
GECCO
2004
Springer
244views Optimization» more  GECCO 2004»
16 years 8 days ago
Using Clustering Techniques to Improve the Performance of a Multi-objective Particle Swarm Optimizer
In this paper, we present an extension of the heuristic called “particle swarm optimization” (PSO) that is able to deal with multiobjective optimization problems. Our approach ...
Gregorio Toscano Pulido, Carlos A. Coello Coello
GECCO
2006
Springer
137views Optimization» more  GECCO 2006»
15 years 10 months ago
A unified optimization framework for microelectronics industry
In this paper, an object-oriented unified optimization framework (UOF) for general problem optimization is proposed. Based on evolutionary algorithms, numerical deterministic meth...
Yiming Li, Cheng-Kai Chen, Yen-Yu Cho
WSC
2008
15 years 9 months ago
A rate result for simulation optimization with conditional value-at-risk constraints
We study a stochastic optimization problem that has its roots in financial portfolio design. The problem has a specified deterministic objective function and constraints on the co...
Soumyadip Ghosh
FS
2006
81views more  FS 2006»
15 years 6 months ago
Optimal portfolio choice in the bond market
We consider the Merton problem of optimal portfolio choice when the traded instruments are the set of zero-coupon bonds. Working within an infinite-factor Markovian Heath-Jarrow-Mo...
Nathanael Ringer, Michael Tehranchi