The choice of the selection method used in an evolutionary algorithm may have considerable impacts on the behavior of the entire algorithm. Therefore, earlier work was devoted to t...
We develop a memory-efficient off-line algorithm for the enumeration of global states of a distributed computation. The algorithm allows the parameterization of its memory requir...
We investigate the problem of non-covariant behavior of policy gradient reinforcement learning algorithms. The policy gradient approach is amenable to analysis by information geom...
Matrix optimization with orthogonal constraints appear in a variety of application fields including signal and image processing. Several researchers have developed algorithms for...
A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...