In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
In this paper we propose a hybrid system that bridges the gap between traditional image processing methods, used for low-level object recognition, and abductive constraint logic pr...
Imagine some program and a number of changes. If none of these changes is applied (“yesterday”), the program works. If all changes are applied (“today”), the program does n...
ASTRAL is a high-level formal specification language for real-time (infinite state) systems. It is provided with structuring mechanisms that allow one to build modularized specifi...
Federated transaction management (also known as multidatabase transaction management in the literature) is needed to ensure the consistency of data that is distributed across mult...