We consider a network of sensors deployed to sense a spatio-temporal field and infer parameters of interest about the field. We are interested in the case where each sensor's...
S. Sundhar Ram, Venugopal V. Veeravalli, Angelia N...
Planning methods for deterministic planning problems traditionally exploit factored representations to encode the dynamics of problems in terms of a set of parameters, e.g., the l...
We discuss the problem of finding a good state representation in stochastic systems with observations. We develop a duality theory that generalizes existing work in predictive sta...
Christopher Hundt, Prakash Panangaden, Joelle Pine...
The paper describes a framework in the form of an optimization of a performance index subject to the constraints of a dynamic network, represented in the state space. The performa...
We consider in the current paper the issue of exploiting the structural form of Esterel programs [BG92] to partition the algorithmic RSS (reachable state space) fix-point construc...