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...
One of the major difficulties when applying Multiobjective Evolutionary Algorithms (MOEA) to real world problems is the large number of objective function evaluations. Approximate...
— 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...
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...
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...