@article{2/99,
author = "Gonz{\'a}lez, Jos{\'e} Carlos and Velasco, Juan Ram{\'o}n and Iglesias, Carlos A.",
abstract = "Hybridization of connectionist and symbolic systems is being proposed for machine learning purposes in many applications for different fields. However, a unified framework to analyse and compare learning methods has not appeared yet. In this paper, a multiagent-based approach is presented as an adequate model for hybrid learning. This approach is built upon the concept of bias.",
booktitle = "ENGINEERING APPLICATIONS OF BIO-INSPIRED ARTIFICIAL NEURAL NETWORKS, VOL II",
comments = "JCR Q2",
doi = "10.1007/BFb0100471",
impact_factor = "0.515",
issn = "0302-9743",
keywords = "hybrid;machine learning;agent",
pages = "50-57",
publisher = "Springer Verlag",
title = "{A}n {A}gent-{B}ased {O}perational {M}odel for {H}ybrid                   {C}onnectionist-{S}ymbolic {L}earning",
url = "http://link.springer.com/content/pdf/10.1007%2FBFb0100471",
volume = "0302-9743",
year = "1999",
}