Partially observable Markov decision process (POMDP) is commonly used to model a stochastic environment with unobservable states for supporting optimal decision making. Computing ...
We present a reduction of a large-scale network model of visual cortex developed by McLaughlin, Shapley, Shelley, and Wielaard. The reduction is from many integrate-and-fire neuron...
In this paper we present a new technique to simulate polymer blends that overcomes the shortcomings in polymer system modeling. This method has an inherent advantage in that the v...
This paper deals with multidimensional ICA and its performance analysis, applied to cosmological observations. Our purpose is the separation of the cosmic microwave background rad...
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...