@inproceedings{571070522c8e4a759dcc0afd575d0a72,
title = "Homeostatic robot control using simple neuromodulatory techniques",
abstract = "The UESMANN (Uniform Excitatory Switching Multifunction Artificial Neural Network) architecture has been shown to produce interesting transitions between multiple behaviours using an extremely simple neuromodulatory regime. Previous work has concentrated on discrete classification tasks. In this work, three different simple neuromodulatory architectures including UESMANN are used to control a robot in a homeostatic task. The experiments show that UESMANN produces interesting and useful transitional behaviour in an embodied system, learning the two tasks in the same number of parameters (i.e. network weights) as networks which learned each individual task.",
keywords = "Backpropagation, Long-term autonomy Homeostasis, Neural network, Neuromodulation, Robotics",
author = "Finnis, {James C.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017.; 18th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2017 ; Conference date: 19-07-2017 Through 21-07-2017",
year = "2017",
month = jul,
day = "19",
doi = "10.1007/978-3-319-64107-2_26",
language = "English",
isbn = "9783319641065",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "325--339",
editor = "Yang Gao and Saber Fallah and Yaochu Jin and Constantina Lekakou",
booktitle = "Towards Autonomous Robotic Systems - 18th Annual Conference, TAROS 2017, Proceedings",
address = "Switzerland",
}