@inproceedings{40bfc551db05420fa51d448aa5d6406c,
title = "Selection Of auxiliary objectives in artificial immune systems: Initial explorations",
abstract = "Multi-objectivization of artificial immune systems (AIS) is considered for several discrete optimization problems with certain properties. It is performed by adding auxiliary objectives which are selected online using reinforcement learning. The results suggest that using auxiliary objectives may help to improve performance of AIS. It is also shown that reinforcement learning is able to ignore inefficient auxiliary objective in AIS, as it is in EA. To the best of our knowledge, this is the first attempt to study effects of multi-objectivization on AIS.",
keywords = "BCA, Helper-objectives, Multi-objectivization, Reinforcement learning",
author = "Arina Buzdalova and Nina Bulanova",
year = "2015",
language = "English",
volume = "2015-January",
series = "Mendel",
publisher = "Brno University of Technology",
pages = "47--52",
editor = "M. Radek",
booktitle = "21st International Conference on Soft Computing",
address = "Czech Republic",
note = "21st International Conference on Soft Computing: Evolutionary Computation, Genetic Programming, Swarm Intelligence, Fuzzy Logic, Neural Networks, Chaos, Bayesian Methods, Intelligent Image Processing, Bio-Inspired Robotics, MENDEL 2015 ; Conference date: 23-06-2015 Through 25-06-2015",
}