Temporal difference methods are theoretically grounded and empirically effective methods for addressing reinforcement learning problems. In most real-world reinforcement learning ...
High-throughput analytical techniques such as nuclear magnetic resonance, protein kinase phosphorylation, and mass spectroscopic methods generate time dense profiles of metabolites...
Prospero C. Naval, Luis G. Sison, Eduardo R. Mendo...
The banking industry regularly mounts campaigns to improve customer value by offering new products to existing customers. In recent years this approach has gained significant mome...
The goal of our investigation is to find automatically the best rule for a cell in the cellular automata model. The cells are either of type Obstacle, Empty or Creature. Only Crea...
— We consider whether the off-line compilation of a set of Service Level Agreements (SLAs) into low-level management policies can lead to the runtime maximization of the overall ...