— This paper presents the optimal joint filtering and parameter identification problem for uncertain linear stochastic systems with unknown parameters in both state and observa...
Michael V. Basin, Alexander G. Loukianov, Miguel H...
The search for finite-state controllers for partially observable Markov decision processes (POMDPs) is often based on approaches like gradient ascent, attractive because of their ...
We propose a new decision-theoretic approach for solving execution-time deliberation scheduling problems using recent advances in Generalized Semi-Markov Decision Processes (GSMDP...
This paper reports some experiments that compare the accuracy and performance of two stochastic parsing systems. The currently popular Collins parser is a shallow parser whose out...
Ronald M. Kaplan, Stefan Riezler, Tracy H. King, J...
Recruitment learning in hierarchies is an inherently unstable process (Valiant, 1994). This paper presents conditions on parameters for a feedforward network to ensure stable recru...