Learning agents, whether natural or artificial, must update their internal parameters in order to improve their behavior over time. In reinforcement learning, this plasticity is ...
Reinforcement learning models generally assume that a stimulus is presented that allows a learner to unambiguously identify the state of nature, and the reward received is drawn f...
Tobias Larsen, David S. Leslie, Edmund J. Collins,...
In a public cloud, bandwidth is traditionally priced in a pay-asyou-go model. Reflecting the recent trend of augmenting cloud computing with bandwidth guarantees, we consider a n...
Social network analysis has attracted increasing attention in recent years. In many social networks, besides friendship links amongst users, the phenomenon of users associating th...
Background: Structure identification of dynamic models for complex biological systems is the cornerstone of their reverse engineering. Biochemical Systems Theory (BST) offers a pa...
Marco Vilela, Carlos Cristiano H. Borges, Susana V...