The research using artificial intelligence and computer simulation introduces a new approach for solving the job shop-scheduling problem. The new approach is based on the developm...
We consider approximate policy evaluation for finite state and action Markov decision processes (MDP) in the off-policy learning context and with the simulation-based least square...
This paper proposes a new statistical model-based likelihood ratio test (LRT) VAD to obtain reliable speech / non-speech decisions. In the proposed method, the likelihood ratio (L...
In many AI fields, the problem of finding out a solution which is as close as possible to a given configuration has to be faced. This paper addresses this problem in a propositiona...
The vast size of real world stochastic programming instances requires sampling to make them practically solvable. In this paper we extend the understanding of how sampling affects ...