@inproceedings{ba871b0aeb3d404390274c7e06dc9607,
title = "Punishment policy adaptation in a road junction regulation system",
abstract = "This paper studies the problem of adapting punishment policies in traffic scenarios. It focuses on a two-road junction scenario simulated by means of Simma, a Multi-Agent Based Simulation Tool. Adaptation is based on an adaptive neuro-fuzzy inference system (ANFIS) together with a hybrid learning algorithm (HLA). Basic punishment policy is provided through a knowledge base that specifies the conditions that must hold in order to assign different punishments. The aim of this paper is to show how the ANFIS system can improve this policy unsupervisedly.",
keywords = "ANFIS, Multi-Agent System, Policy adaptation, Traffic regulation",
author = "Maite Lopez-Sanchez and Sanja Bauk and Natasa Kovac and Rodriguez-Aguilar, {Juan A.}",
year = "2007",
language = "English",
isbn = "9781586037987",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "112--119",
booktitle = "Artificial Intelligence Research and Development",
address = "Netherlands",
note = "10th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2007 ; Conference date: 25-10-2007 Through 26-10-2007",
}