Berthouze, Luc

Kaplan, Frederic

English

CogPrints Cognitive Sciences Eprint Archive

Introduction: The Fifth International Workshop on
Epigenetic Robotics

Cognitive Sciences ePrint Archive

1Introduction: The Fifth International Workshop on
Epigenetic Robotics
Luc Berthouze
Neuroscience Research Institute
Tsukuba AIST Central 2, Umezono 1-1-1
Tsukuba 305-8568 Japan
Luc.Berthouze@aist.go.jp
Fre´de´ric Kaplan
Sony Computer Science Laboratory
6, Rue Amyot
75005 Paris France
kaplan@csl.sony.fr
1. Introduction
The international workshop on Epigenetic Robotics
has established itself as a forum for multi-disciplinary
research, ranging from developmental psychology to
neural sciences (in its widest sense) and robotics
including computational studies. With contribu-
tions and audience increasingly spreading across dis-
ciplines, the two-fold aim of research in epigenetic
robotics is also becoming increasingly clear. On the
one hand, the proposed systems and models start
showing the characteristics of human development,
and in doing so, gain in robustness and flexibility;
and on the other hand, these systems also establish
themselves as an alternative route to understanding
the brain, cognitive functions, and social develop-
ment.
This year, in an effort to further encourage sub-
missions by the psychology community, we intro-
duced a dual-track (abstract, short-paper) submis-
sion system. Short-papers could be accepted ei-
ther as long papers (to be extended up to 8 pages),
short papers (4 pages) or posters. Forty short pa-
pers and 10 abstracts were submitted. Each con-
tribution received three reviews which resulted in a
technical program with 10 long papers, 8 short pa-
pers, 5 posters (from short paper submissions) and 8
posters (from abstract submissions). The workshop
will also feature five invited talks that reflect the dis-
tribution of topics addressed since the inception of
this series of workshops: robotics and dynamical sys-
tems (Masahiro Fujita), motor learning (Eugene
Goldfield), imitation (TBA), cognitive development
(Annette Karmiloff-Smith), and social interac-
tion (Brian Scassellati).
2. Regular contributions
2.1 Long papers
So-called epigenetic systems/models often show only
one step of development: such systems will typically
acquire one motor skill, or will emerge one cognitive
function. Yet human development is characterized
by what Prince, Helder and Hollich call on-going
emergence, i.e., the continuous development and in-
tegration of new skills. They propose six concrete cri-
teria for a system to exhibit on-going emergence: (1)
continuous skill acquisition, (2) incorporation of new
skills with existing skills, (3) autonomous develop-
ment of values and goals, (4) bootstrapping of initial
skills, (5) stability of skills, and (6) reproducibility.
On-going emergence is exactly what Demiris and
Dearden try to address with HAMMER, a hierar-
chical architecture that implements a principled way
for combining knowledge through exploration and
knowledge from others. They describe a develop-
mental pathway whereby the system can develop hi-
erarchies of increasingly complex inverse models, and
combine both learning through self exploration and
learning from others. Predictive control plays a crit-
ical role in the simulation theory of mind advocated
by those authors. It does so as well in Balkenius
and Johansson’s model of gaze control for the de-
velopment of visual attention. The authors describe
a model of gaze control that includes mechanisms for
predictive control using a forward model and event
driven expectations of target behavior. They show
the model to roughly undergo stages similar to those
of human infants if the influence of the predictive
systems is gradually increased. Once a visual tar-
get is identified, being able to reach for it is critical.
From a control point of view, however, learning to
reach is saddled with the so-called ’curse of dimen-
sionality’. Sun and Scassellati demonstrate that
sensory information from a vestibular system can be
used to replace a portion of the kinematic chain in-
volved in learning to reach. This replacement has
two benefits: (a) it can result in a decrease of the
dimensionality of the learning problem, and (b) the
errors that are necessarily introduced by this replace-
ment strategy lead to curved reaching trajectories
similar to those observed in human reaches. Hav-
ing the capability to reach objects it sees, a system
can now engage in haptic exploration of objects in its
Berthouze, L., Kaplan, F., Kozima, H., Yano, H., Konczak, J., Metta, G., Nadel, J., Sandini, G., Stojanov, G. and Balkenius, C. (Eds.)
Proceedings of the Fifth International Workshop on Epigenetic Robotics:  Modeling Cognitive Development in Robotic Systems 
Lund University Cognitive Studies, 123.  ISBN 91-974741-4-2 
2environment. This is the focus of Torres-Jara, Na-
tale and Fitzpatrick’s contribution. They adopt a
bottom-up approach to adapting and learning about
the environment. Rather than providing the system
with abilities that would enable the robot to accom-
plish specific tasks, they provide it with a generic
ability: tapping. The repetitive, redundant, cross-
modal nature of tapping gives the robot an oppor-
tunity to reliably identify when the sound of contact
with the object occurs, and to collect samples of that
sound. The authors demonstrate the utility of this
exploratory procedure for a simple object recogni-
tion scenario. Now, how would a robot understand
whether it is touching an object or itself? That’s
the question Edsinger-Gonzales tries to answer.
His robot learns to disciminate between ego and exo
forces purely on the basis of its proprioceptive sense
of force, through a series of semi-autonomous devel-
opmental stages.
Two papers round up this series of motor-related
papers. In the first one, Konczak continues on last
year’s keynote with a review of two reflexive motor
patterns in humans: Primitive reflexes and motor
primitives. He argues that an understanding (and
modelling?) of the human motor system that encom-
passes both primitive reflexes and motor primitives
as well as the interaction with supraspinal motor cen-
ters is critical to the design of epigenetic robots.
Indeed, understanding the mechanisms (change in
connectivity? internal clock mechanism?) by which
the primitive motor system is being integrated with
later maturing supraspinal motor centers to give rise
to complex motor behaviors should be most benefi-
cial for robots to acquire complex motor skills in a
bottom-up approach. In the second paper, Veskos
and Demiris revisit a study published by Berthouze
and Lungarella in a previous edition of the workshop
on swinging and the degrees of freedom problem. Us-
ing a different formalism of central pattern genera-
tors, the authors successfully apply the same prin-
ciple of entrainment to acquiring two motor skills:
swinging and walking.
Finally, two papers deal with much higher cog-
nitive tasks but still within the context of the sys-
tem’s sensory inputs. Lacerda et al. attempt to
interpret the infant’s first steps in the acquisition of
the ambient language as a consequence of the in-
fant’s general capacity to represent sensory input
and the infant’s interaction with other actors in its
immediate ecological environment. The authors ar-
gue that their Ecological Theory of Language Ac-
quisition (ETLA), which they presented last year,
offers a productive alternative to traditional descrip-
tive views of the language acquisition process by pre-
senting an operative model of how early linguistic
function may emerge through interaction. Finally,
Blanchard and Can˜amero discuss a perception-
action architecture for imprinting – the establish-
ment of strong attachment links between robot and
caregiver. Imprinting allows adaptation as a result of
reward-based learning in the context of a history of
affective interactions between the robot and the hu-
man. This certainly is an ability an epigenetic robot
will need in order to proceed further in its social de-
velopment.
2.2 Short papers
Building on their previous work on homeostatic be-
haviors, Andry, Gaussier, and Nadel propose a
neural architecture for sequence learning, an impor-
tant component for an imitating system. In their
architecture, demonstration and reproduction stages
are fused, with learning occuring when the system is
not in an equilibrium.
Vitay proposes a computational model for a sys-
tem to learn to count objects. An interesting par-
ticularity of his model is that this ability is realized
from the merging, via a common reward signal, of
two independent computational models: a model for
switching spatial visual attention, and a model for
learning the ordinal sequence of phonetical numbers.
Olsson, Nehaniv, and Polani continue with
their research on the issue of how many sensory sys-
tems adapt to the environment. This year, they have
a robot learn how correlations over time in the sen-
sors are related to the actuators’ activities. With this
approach, a robot can develop from unknown sensors
and actuators to being able to perceive motion.
Van Dartel and Postma investigate whether
symbol manipulation, the hallmark of traditional
cognitive science, can be achieved by robots with the
ability to simulate perception and behaviour inter-
nally. As a case-study they investigate how and why
internal simulation in a Situated Tower of London
task improves performance in the Tower of London
task, and compare system and human performance.
In an interesting attempt towards achieving on-
going emergence, Clowes and Morse look at lan-
guage as a way to not only speed up the acquisi-
tion of normal behaviours, but also to further enable
successful operation at tasks beyond the original ca-
pabilities of the agent. Investigating the Vygotskian
idea that language plays a role in intimately structur-
ing the learning environment, allowing the construc-
tion of more complex cognitive activities, the authors
describe experiments with evolved agents that use
self-directed speech and show that they achieve high
fitness more rapidly than agents that don’t.
Huang and Weng describe a reinforcement-
based model for a robot to develop its covert per-
ceptual capability (the selection of an action by a
value system). The method is tested in a non-trivial
vision-based navigation task.
Finally, in a contribution that nicely complements
3that of Prince et al.,Metta, Vernon, and Sandini
outline an agenda for the RobotCub project which
could very well be an agenda for our entire commu-
nity.
2.3 Posters
Understanding the development of joint attention is
a crucial issue for research in epigenetic robotics.
Prior studies in developmental psychology argue that
skills underlying joint attention do not emerge until
9 month of age. Stahl and Striano present a longi-
tudinal experimental study with sixteen infants from
7 to 10 months of age. Their results seem to indicate
that such skills gradually unfold before 9 months of
age. These findings that go in favor of a gradual de-
velopment give encouraging support for robotic mod-
els that try to reenact the developmental trajectory
towards joint attention. To achieve joint attention
between machines using artificial vision systems, seg-
mentation stability is often a key issue. Baillie and
Nottale describe a way to measure the stability of a
segmentation algorithm and present experimental re-
sults obtained with several algorithms under various
forms of image distortion.
How can robots and computational models help
understanding developmental disorders like autism?
Bjo¨rne and Balkenius have worked for a few years
on a computational theory of autism. This year, they
investigate the role of context in motor impairments
for children with autism. They present a specula-
tive view arguing that an inability to take contex-
tual factors into account could explain some charac-
teristic motor impairment in autism. From another
perspective,Miyamoto, Lee, Fujii and Okada in-
vestigate how robots can facilitate interaction with
autistic children. They present results of a longi-
tudinal study with five children interacting with a
speaking robot in two situations. They discuss in
particular the cases of two children who showed de-
velopmental change in interacting with the robot.
How does an infant develop the ani-
mate/inanimate distinction? What underlie
the feeling of animacy? Kuwamura, Yamamoto
and Hashimoto discuss the relationship between
movement and animacy with a psychophysical
experiment where dynamical systems are designed
using an interactive evolution method. Their results
suggest that oscillations and stroke movements are
key perceptual factors underlying the feeling of
animacy.
Bredeche and Hugues investigate the issue of
open development from an evolutionary robotics per-
spective. They suggest to define stages of increasing
complexity in order to evolve increasingly complex
controllers. For this purpose, they define an environ-
ment generator that automatically produces environ-
ments of adapted complexity. They present prelim-
inary experimental results showing the efficiency of
this approach compared to standard fitness criteria.
By sharing environmental sounds, humans and
robots can share information on the environment.
Unfortunately, it is difficult for humans and robots
to communicate such sounds. Hattori et al. sug-
gest to acquire a multi-modal mapping from sound
to motion (the motion performed by the object that
produced the sound) by learning from temporal con-
tingencies. The robot can then imitate the motion
using its body.
Aryananda placed her humanoid head robot with
two basic in-built behaviors (tracking of faces and
bright objects, mimicking of phoneme sequences) in
an open-ended environment and tried to find out
what the robot could see, and what it could hear.
Results show that there was enough ”interesting” in-
formation for the robot to start unsupervised lexical
acquisition for example.
Mirza, Nehaniv, te Boekhorst, and Daut-
enhahn show that information theoretical methods
can be used for a robot to characterize its inter-
actions and interaction history. In particular, the
authors show that fractal dimension of the sensory-
motor phase plot is a useful measure.
Prepin, Gaussier, Revel, and Nadel briefly
outline the basic principles of a formal approach –
the Cognitive System Formalism – to represent, ana-
lyze and compare cognitive systems of developmental
robotics and psychology.
Finally, Oka and Ozaki describe RobotPHONE,
a simple robotic platform designed for educational
purposes. By using a software SDK, students can ex-
periment with associative learning systems and build
easily simple epigenetic systems.
Thanks
We thank the National Institute of Communication
Technology (NICT) of Japan for their generous sup-
port of this workshop, and Hideki Kozima in partic-
ular for dealing with the local organization and with
the administrative side of the organization. Finally,
we also thank the program committee members for
their efforts in reviewing submissions.


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