Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Abstract. Regular model checking is a form of symbolic model checking technique for systems whose states can be represented as finite words over a finite alphabet, where regular ...
Abstract. We present a probability logic (essentially a first order language extended with quantifiers that count the fraction of elements in a model that satisfy a first order ...
The need for mining causality, beyond mere statistical correlations, for real world problems has been recognized widely. Many of these applications naturally involve temporal data...
— The communication sub-system of complex IC systems is increasingly critical for achieving system performance. Given this, it is important that the on-chip communication archite...