Properly-designed bulk-loading techniques are more efficient than the conventional tuple-loading method in constructing a multidimensional index tree for a large data set. Although...
Gang Qian, Hyun-Jeong Seok, Qiang Zhu, Sakti Prama...
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Reinforcement Learning methods for controlling stochastic processes typically assume a small and discrete action space. While continuous action spaces are quite common in real-wor...
Although evolutionary algorithms (EAs) are widely used in practical optimization, their theoretical analysis is still in its infancy. Up to now results on the (expected) runtime ar...
We target the problem of closed-loop learning of control policies that map visual percepts to continuous actions. Our algorithm, called Reinforcement Learning of Joint Classes (RLJ...