Within the context of two sets of robotic experiments we have performed, we examine some representational and algorithmic issues that need to be addressed in order to equip robots with the capacity to imitate. We suggest that some of the di culties might be eased by placing imitation architectures within a wider social context

Demiris, Y

Hayes, G

Within the context of two sets of robotic experi-ments we have performed, we examine some rep-resentational and algorithmic issues that need to be addressed in order to equip robots with the capacity to imitate. We suggest that some of the difficulties might be eased by placing imitation architectures within a wider social context

John Demiris

Gillian Hayes

CiteSeerX

Do robots ape

Spiral - Imperial College Digital Repository

Do Robots Ape?John Demiris and Gillian HayesDepartment of Articial IntelligenceUniversity of Edinburgh5 Forrest Hill, Edinburgh, EH1 2QL, Scotland, UKjohnde@dai.ed.ac.uk, gmh@dai.ed.ac.ukAbstractWithin the context of two sets of robotic experi-ments we have performed, we examine some rep-resentational and algorithmic issues that need tobe addressed in order to equip robots with thecapacity to imitate. We suggest that some of thediculties might be eased by placing imitationarchitectures within a wider social context.IntroductionRobot designers are frequently faced with a problemwhich could be seen as an instance of the Nature vsNurture debate, commonly found in the natural sci-ences: while there seems to be a general consensus thattabula rasa algorithms for robot learning are unlikelyto be successful, robot designers tend to agree that pre-imposing their own perceptions on the robot's controlstructure might prove counterproductive as they strivetoward more adaptive robots.Recently, imitation, which is seen as an importantmethod of learning in the animal kingdom (Whiten andHam, 1992), has been proposed as a promising methodfor a compromise between the two approaches. Whilethe robot architecture is designed in order to benetfrom other agents' knowledge, this is done "from theinside", i.e. the robot learns about the world basedon its own perceptions. Imitation can be used as aguide [shaping process] for the robot during its socialdevelopment in human and robot societies.The issuesWhere do we start? We believe that in order for arobot to be able to imitate, the following should betaken into account: There are several dierent levels of imitation, whichdo not necessary share the same underlying mech-anisms. We see at least three levels:(A) Basic imitation as reproduction of the perceivedstimulus, for example, imitation of body move-ments or speech sounds.(B) Functional imitation, for example picking-upan object, moving towards a door, making a soundto scare o a predator, etc. Essentially, in thislevel, its not the exact stimulus that is being im-itated but rather the eect that it has.(C) Abstract imitation or social attunement, i.e.imitation not of the external action but of the pre-sumed internal state of the partner (for example,making a sad face when another one is crying,smiling when others laugh).A mechanism is needed to dynamically select thelevel that the robot should imitate according to thecurrent social conditions and its own current needsand purposes (depending on whether imitation iscurrently a game, or a method of cutting down asearch space, or a method for achieving social ac-ceptance, among others). Imitation might not bepossible at all levels at all times (unless elementsof prediction are incorporated in the architecture),since frequently the purpose of an action might notbe apparent at its onset. The robot should have a concept of its own bodyand of the body of the agent it is trying to imitate.These robot body images do not necessarily needto be designed in, and can be learned. We envisagethat the two body images and their development willbe closely linked (if not being instances of the samebody schema), and in our work (Demiris and Hayes,1996) we have suggested that this might be done ina distributed, topography-preserving way. Since the robot is perceiving its own body mainlythrough proprioception (and frequently through vis-ion), while it is perceiving the other agent's throughthe external senses, there must exist a cross-modalPreprint version; final version available at www.aaai.orgAAAI Fall Symposium on Socially Intelligent Agents (1997), pp: 28-30matching mechanism that will perceive equival-ences between the two modalities, and can translatebetween the two. There are two dierent forms of learning associ-ated with imitation: learning to imitate and learningthrough imitation. In the former, the robot learnswhat its motor system has to do in order to do whatthe other agent is doing. In the latter, the robotlearns by imitating the other agent, and associatingperceptual experiences (environmental ones, and/orown ones, such as emotions, biological feedback fromits own organism, among others) with this motor act.Robot Imitation ExamplesWe have performed two series of robot imitation ex-periments. One of them was performed on testbedsinvolving dierent types of robot heads and a humandemonstrator (Demiris and Hayes, 1996; Demiris et al,1997), where the experiments were aimed at examiningthe issues involved in movement imitation. The otherseries (Hayes and Demiris, 1994) involved two mobilerobots of dierent morphology, where the experimentswere aimed at examining the issues involved in learningthrough movement imitation.Movement ImitationWe are interested in understanding the mechanismsunderlying imitation of movements in 3D space, sowe engaged in a series of experiments involving a ro-bot head imitating the head movements of a humandemonstrator. The demonstrator performs a series ofhead movements positioned within the visual eld ofthe robot head, and the robot imitates these move-ments. The technical details of these experiments aredescribed in (Demiris and Hayes, 1996; Demiris et al,1997); here we will focus on an issue particularly rel-evant to our discussion: due to the experimental scen-ario used, there will be dierent modalities involvedduring the perception and the execution of a move-ment pattern (the visual modality during perceptionand the proprioceptive modality during execution).This points out the necessity of designing a mechan-ism for bridging the two. In humans, such mechanismshave been hypothesised to exist at birth (Meltzo andMoore, 1989), although several questions regarding thespecics of such mechanisms remain unresolved. Forexample, is the information derived from one modalitytransferred to the other one directly or is it stored insome intermediate a-modal representation? The seg-mentation of the input data (including the selectionof the level to imitate, mentioned earlier, which hasa strong inuence on how the incoming data will besegmented) is one of the most dicult problems thatthe robot controller designer is facing. However, thestudy of imitation in natural systems is helping to re-solve some of the diculties, by suggesting that thegenerative system is actively involved in the recogni-tion process. For example, recent neurophysiologicalresearch (Rizzollati et al, 1996) has indicated a stronglink between the recognition and generation processes,at the neuronal level, through the discovery of `mirror'neurons in the premotor cortex of monkeys, which areactivated both during perceiving and executing cer-tain actions. That means that the imitator's previousbodily experience inuences the way it perceives thedemonstrator's actions. Apart from reiterating the factthat past knowledge inuences the way that current in-formation is processed, this work emphasizes the roleof embodiment in the way cognitive processes operate(Dautenhahn, 1997; Mataric, 1996).Learning through Movement ImitationIn this series of experiments, the purpose was to in-vestigate how a robot can learn to negotiate the dif-ferent types of corners in order to navigate througha maze. While one agent is knowledgeable about thetask, the other is not, and is only equipped with theability to imitate (follow) the rst agent. The agentsare placed in a maze, the rst agent traverses the maze,and the second one follows right behind, associatingthe environmental states with the motor actions it isperforming due to its imitation of the teacher. Wewill focus on a couple of important issues which arerelevant to our discussion here that were made evid-ent during this work (interested readers are referred to(Hayes and Demiris, 1994) for the details). These areessentially linked with the temporal dimension of thetask. The rst one of them is when to imitate: it isimportant for the imitator not to imitate the actionsof the demonstrator (such as turning left or right in acorner) immediately, but rather when the imitator ac-tually reaches that corner. The answer to this questionmight be task-specic, which implies that the imitatorhas to have some knowledge of the task in hand. Thesecond one is when to associate what you perceive withwhat you do. Although some aspects of the answer tothis are also task-specic, a partial solution might begiven through the use of `novelty detectors', which linkthe current action with previous knowledge that theimitator might have.Supporting the Imitation ProcessImitation is rarely a uni-directional activity, nor oc-curs in the absence of other learning processes. In-fants and young children, not only imitate their parentsand other peers, but are frequently imitated by them(Meltzo, 1996), often engaging in mutual imitationPreprint version; final version available at www.aaai.orgAAAI Fall Symposium on Socially Intelligent Agents (1997), pp: 28-30games. There is also a close link between imitation,communication and cooperation (Klingspor, Demiris,and Kaiser, 1997): not only imitation can be used asa good way of developing communication (Billard andHayes, 1997), and equipping the imitator with enoughknowledge about a task so it can eventually engagein cooperation with other agents, but, reversely, com-munication can also help in the imitation process byinuencing the way that the imitator understands thetask in hand, so an appropriate level of imitation canbe selected. For example, the imitator's action can bemonitored by the demonstrator who can give feedbackto the imitator on the quality of the imitation (provid-ing the imitator with opportunities to learn how toimitate), but also on two crucial aspects mentionedabove, when to imitate, and when to associate.Learning by imitation is frequently combined withother learning processes, in which case the imitationprocess can help speeding them (e.g. (Schaal, to ap-pear)). In addition, as we frequently mentioned in thispaper, the imitator's own knowledge and capabilities,partially obtained by processes other than imitation(including trial and error learning), inuence (hope-fully facilitate) the way that the imitation process willtake place.These suggest that placing imitation architectureswithin a wider social learning context might help ussolve some of the dicult issues in robot imitation thatwe outlined in this paper. If we want our robots toachieve the degree of imitation displayed in natural so-cieties, we have to provide the robots with comparablelevels of social support.AcknowledgementsJ Demiris is supported by a European Science Found-ation fellowship in the program "Learning in Humansand Machines - TF5: Collab. Learning". Thanks to ABillard and J Wyatt for their comments on this paper.ReferencesBillard A. and Hayes G.M., 1997. Learning to Com-municate through Imitation in Autonomous robots. InProc. of the 7th International Conference on Arti-cial Neural Networks (ICANN97), Lausanne, Oct 97,Switzerland.Dautenhahn K., 1997. I could be you - the phenomen-ological dimension of social understanding. In Cyber-netics and Systems Journal, Special Issue on Epistem-ological Aspects of Embodied AI, 28(5), 417-453.Demiris, J., and Hayes, G.M., 1996. Imitative Learn-ing Mechanisms in Robots and Humans. In Proc. ofthe 5th European Workshop on Learning Robots, V.Klingspor (ed.), Bari, Italy, July 1996.Demiris, J.; Rougeaux, S.; Hayes G.; Berthouze L.;Kuniyoshi, Y., 1997. Deferred Imitation of HumanHead Movements by an Active Stereo Vision Head. InProc. of the 1997 IEEE Workshop on Robot-HumanCommunication, Sendai, Japan, Sept. 1997.Hayes, G.M., and Demiris J., 1994. A Robot Control-ler Using Learning by Imitation. In Proc. of the 2ndInternational Symposium on Intelligent Robotic Sys-tems, Grenoble, France, July 1994.Klingspor V., Demiris J., and Kaiser M., 1997.Human-Robot-Communication and Machine Learning.In Applied Articial Intelligence Journal, Vol. 11, toappear (1997).Mataric M.J., 1997. Studying the Role of Embodimentin Cognition. In Cybernetics and Systems Vol. 28, No.6, special issue on Epistemological Aspects of Embod-ied AI, Erich Prem, ed., July 1997.Meltzo, A.N., 1996. The Human Infant as ImitativeGeneralist: A 20-Year Progress Report on Infant Im-itation with Implications for Comparative Psychology.In Social Learning in Animals: The Roots of Culture,Heyes C.M. and Galef B.G. (eds), New York: Aca-demic Press.Meltzo A.N., and Moore M.K., 1989. Imitation inNewborn Infants: Exploring the Range of GesturesImitated and the Underlying Mechanisms. In Devel-opmental Psychology , 25:6, pp. 954-962.Rizzolatti G.; Fadiga L.; Gallese V.; Fogassi L., 1996.Premotor cortex and the recognition of motor neurons.In Cognitive Brain Research, 3, 131-141.Schaal, S. (to appear). Learning From Demonstration.Advances in Neural Information Processing Systems 9,to appear.Whiten A. and Ham R., 1992. On the Nature andEvolution of Imitation in the Animal Kingdom: Re-appraisal of a Century of Research In Advances in theStudy of Behaviour, 21, pp. 239-83.Available Demonstrations and papersVideo clips and papers on this and related work can befound at http: // www.dai.ed.ac.uk / students / johnde/ research.htmlPreprint version; final version available at www.aaai.orgAAAI Fall Symposium on Socially Intelligent Agents (1997), pp: 28-30

English

Do Robots Ape?

Within the context of two sets of robotic experi-ments we have performed, we examine some rep-resentational and algorithmic issues that need to be addressed in order to equip robots with the capacity to imitate. We suggest that some of the diculties might be eased by placing imitation architectures within a wider social context

http://aaaipress.org/Papers/Symposia/Fall/1997/FS-97-02/FS97-02-007.pdf

Do Robots Ape?

Abstract

Similar works

Full text

Available Versions

CiteSeerX

Spiral - Imperial College Digital Repository

CiteSeerX