We describe a novel integration of Planning with Probabilistic State Estimation and Execution resulting in a unified representational and computational framework based on declarat...
Conor McGann, Frederic Py, Kanna Rajan, John Ryan,...
The paper deals with a simulation study on a planned production plant in the brick industry. We implemented this plant in TAYLOR II. Although the boundary conditions seemed relati...
We formalize a model for supervised learning of action strategies in dynamic stochastic domains and show that PAC-learning results on Occam algorithms hold in this model as well. W...
We consider the formulation and analysis of a problem of automatic control: correcting for the distortion induced in an optical wave front due to propagation through a turbulent a...
Eric W. Justh, P. S. Krishnaprasad, M. A. Vorontso...
Abstract--Recurrent neural networks have become a prominent tool for optimizations including linear or nonlinear variational inequalities and programming, due to its regular mathem...