Novelty and Habituation: the Driving Forces in Early Stage Learning for Developmental Robotics

Qinggang Meng, Mark Lee

Research output: Chapter in Book/Report/Conference proceedingChapter

9 Citations (SciVal)


Biologically inspired robotics offers the promise of future autonomous devices that can perform significant tasks while coping with noisy, real-world environments. In order to survive for long periods we believe a developmental approach to learning is required and we are investigating the design of such systems inspired by results from developmental psychology. Developmental learning takes place in the context of an epigenetic framework that allows environmental and internal constraints to shape increasing competence and the gradual consolidation of control, coordination and skill. In this paper we describe the use of novelty and habituation as the motivation mechanism for a sensory-motor learning process. In our system, a biologically plausible habituation model is utilized and the effect of parameters such as habituation rate and recovery rate on the learning/development process is studied. We concentrate on the very early stages of development in this work. The learning process is based on a topological mapping structure which has several attractive features for sensory-motor learning. The motivation model was implemented and tested through a series of experiments on a working robot system with proprioceptive and contact sensing. Stimulated by novelty, the robot explored its egocentric space and learned to coordinate motor acts with sensory feedback. Experimental results and analysis are given for different parameter configurations, proprioceptive encoding schemes, and stimulus habituation schedules.
Original languageEnglish
Title of host publicationBiomimetic Neural Learning for Intelligent Robots
Subtitle of host publicationIntelligent Systems, Cognitive Robotics, and Neuroscience
EditorsStefan Wermter, Gunther Palm, Mark Elshaw
PublisherSpringer Nature
ISBN (Electronic)978-3-540-31896-5
ISBN (Print)0302-9743
Publication statusPublished - 2005

Publication series

NameLecture Notes in Computer Science


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