In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Abstract. We present a new technique called Monotonic Partial Order Reduction (MPOR) that effectively combines dynamic partial order reduction with symbolic state space exploration...
In this paper we study the problem of mining frequent sequences satisfying a given regular expression. Previous approaches to solve this problem were focusing on its search space,...
Structural constraint solving allows finding object graphs that satisfy given constraints, thereby enabling software reliability tasks, such as systematic testing and error recove...