Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
We propose a framework for defining agent-based models (ABMs) and two algorithms for the automatic parallelization of agent-based models, a general version P-ABMG for all ABMs def...
In this paper is presented a new model for data clustering, which is inspired from the selfassembly behavior of real ants. Real ants can build complex structures by connecting the...
Hanene Azzag, Gilles Venturini, Antoine Oliver, Ch...
Independent component analysis (ICA) aims to recover a set of unknown mutually independent source signals from their observed mixtures without knowledge of the mixing coefficients...
This paper describes several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent. The aim is to enhance learning speed and fin...