Abstract. Bilevel optimization problems require every feasible upperlevel solution to satisfy optimality of a lower-level optimization problem. These problems commonly appear in ma...
Many real-world problems are multi-objective optimization problems and evolutionary algorithms are quite successful on such problems. Since the task is to compute or approximate t...
A new method for optimizing complex functions and systems is described that employs Learnable Evolution Model (LEM), a form of non-Darwinian evolutionary computation guided by mac...
Ryszard S. Michalski, Janusz Wojtusiak, Kenneth A....
Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
Estimation-of-distribution algorithm using Cauchy sampling distribution is compared with the bi-population CMA evolutionary strategy which was one of the best contenders in the bl...