The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
R-max is a very simple model-based reinforcement learning algorithm which can attain near-optimal average reward in polynomial time. In R-max, the agent always maintains a complet...
This paper proposes an extension to theorem proving interfaces for use with proofdirected debugging and other disproof-based applications. The extension is based around tracking a...
— In this paper, we evaluate the performance of adaptive algorithms for selecting the number of redundant packets by jointly considering the forward error correction (FEC) and au...
(m,k)-firm constraints have been used to schedule tasks in soft/firm real-time systems under overloaded conditions. In general, they are provided by application designers to guara...