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...
We consider optimization problems that can be formulated as minimizing the cost of a feasible solution wT x over an arbitrary combinatorial feasible set F {0, 1}n . For these pro...
Real-time schedulability theory requires a priori knowledge of the worst-case execution time (WCET) of every task in the system. Fundamental to the calculation of WCET is a schedu...