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FOCS
2006
IEEE
14 years 23 days ago
New Results for Learning Noisy Parities and Halfspaces
We address well-studied problems concerning the learnability of parities and halfspaces in the presence of classification noise. Learning of parities under the uniform distributi...
Vitaly Feldman, Parikshit Gopalan, Subhash Khot, A...
GECCO
2008
Springer
363views Optimization» more  GECCO 2008»
13 years 7 months ago
Towards high speed multiobjective evolutionary optimizers
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
A. K. M. Khaled Ahsan Talukder
ICRA
2005
IEEE
129views Robotics» more  ICRA 2005»
14 years 9 days ago
Dynamic Programming in Reduced Dimensional Spaces: Dynamic Planning For Robust Biped Locomotion
— We explore the use of computational optimal control techniques for automated construction of policies in complex dynamic environments. Our implementation of dynamic programming...
Mike Stilman, Christopher G. Atkeson, James Kuffne...
CORR
2004
Springer
87views Education» more  CORR 2004»
13 years 6 months ago
Exploring tradeoffs in pleiotropy and redundancy using evolutionary computing
Evolutionary computation algorithms are increasingly being used to solve optimization problems as they have many advantages over traditional optimization algorithms. In this paper...
Matthew J. Berryman, Wei-Li Khoo, Hiep Nguyen, Eri...
GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
13 years 10 months ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone