We present a method of distributed model checking of multiagent systems specified by a branching-time temporal-epistemic logic. We introduce a serial algorithm, central to the dis...
The number of states in discrete event systems can increase exponentially with respect to the size of the system. A way to face this state explosion problem consists of relaxing t...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Reflection remains a second-class citizen in current programming models, where it's assumed to be imperative and tightly bound to its implementation. In contrast, most object...
Inferential problems that arise in the empirical analysis oftreatmentresponseinduceambiguityabouttheidentity of optimal treatment rules. This paper describes a research program th...