@InProceedings{Supelec734,
author = {Bassem Khouzam and Hervé Frezza-Buet},
title = {Discovering the phase of a dynamical system from a stream of partial observations with a multi-map self-organizing architecture},
year = {2011},
booktitle = { COGNITIVE 2011},
month = {sep},
address = {Rome (Italy)},
url = {http://www.metz.supelec.fr/metz/personnel/frezza/Papers/KhouzamCognitive11.pdf},
abstract = {This paper presents a self-organizing architecture made of several maps, implementing a recurrent neural network to cope with partial observations of the phase of some dynamical system. The purpose of self-organization is to set up a distributed representation of the actual phase, although the observations received from the system are ambiguous (i.e. the same observation may correspond to distinct phases). The setting up of such a representation is illustrated by experiments, and then the paper concludes on extensions toward adaptive state representations for partially observable Markovian decision processes.}
}