The notion of distributed functional monitoring was recently introduced by Cormode, Muthukrishnan and Yi [CMY08] to initiate a formal study of the communication cost of certain fu...
Chrisil Arackaparambil, Joshua Brody, Amit Chakrab...
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
The paper builds on both a simply typed term system PRω and a computation model on Scott domains via so-called parallel typed while programs (PTWP). The former provides a notion ...
The application of Inductive Logic Programming to scientific datasets has been highly successful. Such applications have led to breakthroughs in the domain of interest and have dri...
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...