In this paper we propose a genetic programming approach to learning stochastic models with unsymmetrical noise distributions. Most learning algorithms try to learn from noisy data...
The definition of “boundary” in the context of multiorganizational information sharing and integration initiatives is developed in the paper. Both current literature and a cas...
Lei Zheng, Tung-Mou Yang, Theresa A. Pardo, Yuanfu...
It is well known that stochastic control systems can be viewed as Markov decision processes (MDPs) with continuous state spaces. In this paper, we propose to apply the policy iter...
This paper presents the qualitative heterogeneous control framework, a methodology for the design of a controlled hybrid system based on attractors and transitions between them. Th...
— The computational understanding of continuous human movement plays a significant role in diverse emergent applications in areas ranging from human computer interaction to phys...