Probabilistic Logic Programming is an active field of research, with many proposals for languages, semantics and reasoning algorithms. One such proposal, Logic Programming with A...
Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Many systems require the setting of a large number of parameters. This is often a difficult and time consuming task, especially for novice users. A framework is presented to simp...
Jarke J. van Wijk, Cornelius W. A. M. van Overveld
Many oil wells in Brazilian onshore fields rely on artificial lift methods. Maintenance services such as cleaning, reinstatement, stimulation and others are essential to these wel...
Dario J. Aloise, Daniel Aloise, Caroline T. M. Roc...
Many machine-learning algorithms learn rules of behavior from individual end users, such as taskoriented desktop organizers and handwriting recognizers. These rules form a “prog...
Todd Kulesza, Simone Stumpf, Margaret M. Burnett, ...