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ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
GECCO
2006
Springer
137views Optimization» more  GECCO 2006»
13 years 11 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
ISCI
2008
159views more  ISCI 2008»
13 years 7 months ago
Large scale evolutionary optimization using cooperative coevolution
Evolutionary algorithms (EAs) have been applied with success to many numerical and combinatorial optimization problems in recent years. However, they often lose their effectivenes...
Zhenyu Yang, Ke Tang, Xin Yao
ROMAN
2007
IEEE
181views Robotics» more  ROMAN 2007»
14 years 2 months ago
Efficient Articulated Model Fitting on a Single Image or a Sequence
Abstract—Models that can efficiently, compactly, and semantically represent potential users are important tools for human-robot interaction applications. We model a person as a p...
Matheen Siddiqui, Gérard G. Medioni
ASC
2011
13 years 2 months ago
Quality of Service constrained routing optimization using Evolutionary Computation
In this work, a novel optimization framework is proposed that allows the improvement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of ...
Miguel Rocha, Pedro Sousa, Paulo Cortez, Miguel Ri...