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Introduction: The Fifth International Workshop on

Epigenetic Robotics

Luc BerthouzeNeuroscience Research Institute

Tsukuba AIST Central 2, Umezono 1-1-1Tsukuba 305-8568 JapanLuc.Berthouze@aist.go.jp

Frederic KaplanSony Computer Science Laboratory

6, Rue Amyot75005 Paris Francekaplan@csl.sony.fr

1. Introduction

The international workshop on Epigenetic Roboticshas established itself as a forum for multi-disciplinaryresearch, ranging from developmental psychology toneural sciences (in its widest sense) and roboticsincluding computational studies. With contribu-tions and audience increasingly spreading across dis-ciplines, the two-fold aim of research in epigeneticrobotics is also becoming increasingly clear. On theone hand, the proposed systems and models startshowing the characteristics of human development,and in doing so, gain in robustness and flexibility;and on the other hand, these systems also establishthemselves as an alternative route to understandingthe 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 atechnical program with 10 long papers, 8 short pa-pers, 5 posters (from short paper submissions) and 8posters (from abstract submissions). The workshopwill also feature five invited talks that reflect the dis-tribution of topics addressed since the inception ofthis series of workshops: robotics and dynamical sys-tems (Masahiro Fujita), motor learning (EugeneGoldfield), 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 onlyone step of development: such systems will typicallyacquire one motor skill, or will emerge one cognitive

function. Yet human development is characterizedby what Prince, Helder and Hollich call on-goingemergence, 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 newskills with existing skills, (3) autonomous develop-ment of values and goals, (4) bootstrapping of initialskills, (5) stability of skills, and (6) reproducibility.On-going emergence is exactly what Demiris andDearden try to address with HAMMER, a hierar-chical architecture that implements a principled wayfor combining knowledge through exploration andknowledge from others. They describe a develop-mental pathway whereby the system can develop hi-erarchies of increasingly complex inverse models, andcombine both learning through self exploration andlearning from others. Predictive control plays a crit-ical role in the simulation theory of mind advocatedby those authors. It does so as well in Balkeniusand Johansson’s model of gaze control for the de-velopment of visual attention. The authors describea model of gaze control that includes mechanisms forpredictive control using a forward model and eventdriven expectations of target behavior. They showthe model to roughly undergo stages similar to thoseof human infants if the influence of the predictivesystems 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 toreach is saddled with the so-called ’curse of dimen-sionality’. Sun and Scassellati demonstrate thatsensory information from a vestibular system can beused to replace a portion of the kinematic chain in-volved in learning to reach. This replacement hastwo benefits: (a) it can result in a decrease of thedimensionality of the learning problem, and (b) theerrors that are necessarily introduced by this replace-ment strategy lead to curved reaching trajectoriessimilar to those observed in human reaches. Hav-ing the capability to reach objects it sees, a systemcan 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

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environment. This is the focus of Torres-Jara, Na-tale and Fitzpatrick’s contribution. They adopt abottom-up approach to adapting and learning aboutthe environment. Rather than providing the systemwith abilities that would enable the robot to accom-plish specific tasks, they provide it with a genericability: tapping. The repetitive, redundant, cross-modal nature of tapping gives the robot an oppor-tunity to reliably identify when the sound of contactwith the object occurs, and to collect samples of thatsound. The authors demonstrate the utility of thisexploratory procedure for a simple object recogni-tion scenario. Now, how would a robot understandwhether it is touching an object or itself? That’sthe question Edsinger-Gonzales tries to answer.His robot learns to disciminate between ego and exoforces purely on the basis of its proprioceptive senseof force, through a series of semi-autonomous devel-opmental stages.

Two papers round up this series of motor-relatedpapers. In the first one, Konczak continues on lastyear’s keynote with a review of two reflexive motorpatterns in humans: Primitive reflexes and motorprimitives. He argues that an understanding (andmodelling?) of the human motor system that encom-passes both primitive reflexes and motor primitivesas well as the interaction with supraspinal motor cen-ters is critical to the design of epigenetic robots.Indeed, understanding the mechanisms (change inconnectivity? internal clock mechanism?) by whichthe primitive motor system is being integrated withlater maturing supraspinal motor centers to give riseto complex motor behaviors should be most benefi-cial for robots to acquire complex motor skills in abottom-up approach. In the second paper, Veskosand Demiris revisit a study published by Berthouzeand Lungarella in a previous edition of the workshopon 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 tointerpret the infant’s first steps in the acquisition ofthe ambient language as a consequence of the in-fant’s general capacity to represent sensory inputand the infant’s interaction with other actors in itsimmediate 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 linguisticfunction may emerge through interaction. Finally,Blanchard and Canamero discuss a perception-

action architecture for imprinting – the establish-ment of strong attachment links between robot andcaregiver. Imprinting allows adaptation as a result ofreward-based learning in the context of a history ofaffective interactions between the robot and the hu-man. This certainly is an ability an epigenetic robotwill 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 aneural architecture for sequence learning, an impor-tant component for an imitating system. In theirarchitecture, demonstration and reproduction stagesare fused, with learning occuring when the system isnot 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 realizedfrom the merging, via a common reward signal, oftwo independent computational models: a model forswitching spatial visual attention, and a model forlearning the ordinal sequence of phonetical numbers.

Olsson, Nehaniv, and Polani continue withtheir research on the issue of how many sensory sys-tems adapt to the environment. This year, they havea robot learn how correlations over time in the sen-sors are related to the actuators’ activities. With thisapproach, a robot can develop from unknown sensorsand actuators to being able to perceive motion.

Van Dartel and Postma investigate whethersymbol manipulation, the hallmark of traditionalcognitive science, can be achieved by robots with theability to simulate perception and behaviour inter-nally. As a case-study they investigate how and whyinternal simulation in a Situated Tower of Londontask improves performance in the Tower of Londontask, 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 enablesuccessful operation at tasks beyond the original ca-pabilities of the agent. Investigating the Vygotskianidea that language plays a role in intimately structur-ing the learning environment, allowing the construc-tion of more complex cognitive activities, the authorsdescribe experiments with evolved agents that useself-directed speech and show that they achieve highfitness 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 avalue system). The method is tested in a non-trivialvision-based navigation task.

Finally, in a contribution that nicely complements

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that of Prince et al., Metta, Vernon, and Sandinioutline an agenda for the RobotCub project whichcould very well be an agenda for our entire commu-nity.

2.3 Posters

Understanding the development of joint attention isa crucial issue for research in epigenetic robotics.Prior studies in developmental psychology argue thatskills underlying joint attention do not emerge until9 month of age. Stahl and Striano present a longi-tudinal experimental study with sixteen infants from7 to 10 months of age. Their results seem to indicatethat such skills gradually unfold before 9 months ofage. These findings that go in favor of a gradual de-velopment give encouraging support for robotic mod-els that try to reenact the developmental trajectorytowards joint attention. To achieve joint attentionbetween machines using artificial vision systems, seg-mentation stability is often a key issue. Baillie andNottale describe a way to measure the stability of asegmentation algorithm and present experimental re-sults obtained with several algorithms under variousforms of image distortion.

How can robots and computational models helpunderstanding developmental disorders like autism?Bjorne and Balkenius have worked for a few yearson a computational theory of autism. This year, theyinvestigate the role of context in motor impairmentsfor 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 anotherperspective, Miyamoto, Lee, Fujii and Okada in-vestigate how robots can facilitate interaction withautistic children. They present results of a longi-tudinal study with five children interacting with aspeaking robot in two situations. They discuss inparticular 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 underliethe feeling of animacy? Kuwamura, Yamamotoand Hashimoto discuss the relationship betweenmovement and animacy with a psychophysicalexperiment where dynamical systems are designedusing an interactive evolution method. Their resultssuggest that oscillations and stroke movements arekey perceptual factors underlying the feeling ofanimacy.

Bredeche and Hugues investigate the issue ofopen development from an evolutionary robotics per-spective. They suggest to define stages of increasingcomplexity in order to evolve increasingly complexcontrollers. 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 ofthis approach compared to standard fitness criteria.

By sharing environmental sounds, humans androbots can share information on the environment.Unfortunately, it is difficult for humans and robotsto communicate such sounds. Hattori et al. sug-gest to acquire a multi-modal mapping from soundto motion (the motion performed by the object thatproduced the sound) by learning from temporal con-tingencies. The robot can then imitate the motionusing its body.

Aryananda placed her humanoid head robot withtwo basic in-built behaviors (tracking of faces andbright objects, mimicking of phoneme sequences) inan open-ended environment and tried to find outwhat the robot could see, and what it could hear.Results show that there was enough ”interesting” in-formation for the robot to start unsupervised lexicalacquisition for example.

Mirza, Nehaniv, te Boekhorst, and Daut-enhahn show that information theoretical methodscan be used for a robot to characterize its inter-actions and interaction history. In particular, theauthors show that fractal dimension of the sensory-motor phase plot is a useful measure.

Prepin, Gaussier, Revel, and Nadel brieflyoutline the basic principles of a formal approach –the Cognitive System Formalism – to represent, ana-lyze and compare cognitive systems of developmentalrobotics and psychology.

Finally, Oka and Ozaki describe RobotPHONE,a simple robotic platform designed for educationalpurposes. By using a software SDK, students can ex-periment with associative learning systems and buildeasily simple epigenetic systems.

Thanks

We thank the National Institute of CommunicationTechnology (NICT) of Japan for their generous sup-port of this workshop, and Hideki Kozima in partic-ular for dealing with the local organization and withthe administrative side of the organization. Finally,we also thank the program committee members fortheir efforts in reviewing submissions.