Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
This paper deals with the modeling and the automatic implementation of constraints in component based applications. Constraints have been assuming an ever more relevant role in mod...
Antonio Coronato, Antonio d'Acierno, Diego D'Ambro...
— Most research in machine learning focuses on scenarios in which a learner faces a single learning task, independently of other learning tasks or prior knowledge. In reality, ho...
Incomplete decision algorithms can often solve larger problem instances than complete ones. The drawback is that one does not know whether the algorithm will finish soon, later, ...
A distinct characteristic of multistate systems (MSS) is that the systems and/or their components may exhibit multiple performance levels (or states) varying from perfect operation...
Suprasad V. Amari, Liudong Xing, Akhilesh Shrestha...