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DAC-H3: a Proactive Robot Cognitive Architecture to Acquire and Express

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DAC-H3: a Proactive Robot Cognitive Architecture to Acquire and Express Preprint version; final version available at http://ieeexplore.ieee.org/ IEEE Transactions on Cognitive and Developmental Systems (Accepted) DOI: 10.1109/TCDS.2017.2754143 1 DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self Clément Moulin-Frier*, Tobias Fischer*, Maxime Petit, Grégoire Pointeau, Jordi-Ysard Puigbo, Ugo Pattacini, Sock Ching Low, Daniel Camilleri, Phuong Nguyen, Matej Hoffmann, Hyung Jin Chang, Martina Zambelli, Anne-Laure Mealier, Andreas Damianou, Giorgio Metta, Tony J. Prescott, Yiannis Demiris, Peter Ford Dominey, and Paul F. M. J. Verschure Abstract—This paper introduces a cognitive architecture for I. INTRODUCTION a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the HE so-called Symbol Grounding Problem (SGP, [1], [2], initiative can originate from both the human and the robot. The T [3]) refers to the way in which a cognitive agent forms an framework, based on a biologically-grounded theory of the brain internal and unified representation of an external word referent and mind, integrates a reactive interaction engine, a number of from the continuous flow of low-level sensorimotor data state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The generated by its interaction with the environment. In this paper, architecture as a whole drives the robot behavior to solve the we focus on solving the SGP in the context of human-robot symbol grounding problem, acquire language capabilities, execute interaction (HRI), where a humanoid iCub robot [4] acquires goal-oriented behavior, and express a verbal narrative of its own and expresses knowledge about the world by interacting with experience in the world. We validate our approach in human- a human partner. Solving the SGP is of particular relevance robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in HRI, where a repertoire of shared symbolic units forms the in real time within a realistic scenario and that it can be used basis of an efficient linguistic communication channel between with naive users. the robot and the human. To solve the SGP, several questions should be addressed: Index Terms—Cognitive Robotics, Distributed Adaptive Con- trol, Human-Robot Interaction, Symbol Grounding, Autobio- • How are unified symbolic representations of external ref- graphical Memory erents acquired from the multimodal information collected by the agent (e.g., visual, tactile, motor)? This is referred Manuscript received December 31, 2016; revised July 25, 2017; accepted to as the Physical SGP [5], [6]. August 09, 2017. The research leading to these results has received funding • How to acquire a shared lexicon grounded in the sensori- from the European Research Council under the European Union’s Seventh motor interactions between two (or more) agents? This is Framework Programme (FP/2007-2013) / ERC Grant Agreement n. FP7-ICT- 612139 (What You Say Is What You Did project), as well as the ERC’s referred to as the Social SGP [6], [7]. CDAC project: Role of Consciousness in Adaptive Behavior (ERC-2013-ADG • How is this lexicon then used for communication and 341196). M. Hoffmann was supported by the Czech Science Foundation under collective goal-oriented behavior? This refers to the Project GA17-15697Y. P. Nguyen received funding from ERC’s H2020 grant agreement No. 642667 (SECURE). T. Prescott and D. Camilleri received functional role of physical and social symbol grounding. support from the EU Seventh Framework Programme as part of the Human This paper addresses these questions by proposing a complete Brain (HBP-SGA1, 720270) project. C. Moulin-Frier, J.-Y. Puigbo, S. C. Low, and P. F. M. J. Verschure are cognitive architecture for HRI and demonstrating its abilities on arXiv:1706.03661v2 [cs.AI] 18 Sep 2017 with the Laboratory for Synthetic, Perceptive, Emotive and Cognitive Systems, an iCub robot. Our architecture, called DAC-h3, builds upon our Universitat Pompeu Fabra, 08002 Barcelona, Spain. P. F. M. J. Verschure is previous research projects in conceiving biologically grounded also with Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST) and Institució Catalana de Recerca cognitive architectures for humanoid robots based on the i Estudis Avançats (ICREA), Barcelona, Spain. Distributed Adaptive Control theory of mind and brain (DAC, T. Fischer, M. Petit, H. J. Chang, M. Zambelli, and Y. Demiris are with presented in the next section). In [8] we proposed an integrated the Personal Robotics Laboratory, Department of Electrical and Electronic Engineering, Imperial College London, SW7 2AZ, U.K. architecture for generating a socially competent humanoid robot, G. Pointeau, A.-L. Mealier, and P. F. Dominey are with the Robot Cognition demonstrating that gaze, eye contact and utilitarian emotions Laboratory of the INSERM U846 Stem Cell and Brain Research Institute, play an essential role in the psychological validity or social Bron 69675, France. U. Pattacini, P. Nguyen, M. Hoffmann, and G. Metta are with the Italian salience of HRI (DAC-h1). In [9], we introduced a unified robot Institute of Technology, iCub Facility, Via Morego 30, Genova, Italy. M. architecture, an innovative Synthetic Tutor Assistant (STA) Hoffmann is also with the Department of Cybernetics, Faculty of Electrical embodied in a humanoid robot whose goal is to interactively Engineering, Czech Technical University in Prague. D. Camilleri, A. Damianou, and T. J. Prescott are with the Department guide learners in a science-based learning paradigm through of Computer Science, University of Sheffield, U.K. A. Damianou is now at rich multimodal interactions (DAC-h2). Amazon.com. DAC-h3 is based on a developmental bootstrapping process Digital Object Identifier 10.1109/TCDS.2017.2754143 where the robot is endowed with an intrinsic motivation to *C. Moulin-Frier and T. Fischer contributed equally to this work. act and relate to the world in interaction with social peers. 2 Preprint version; final version available at http://ieeexplore.ieee.org/ IEEE Transactions on Cognitive and Developmental Systems (Accepted) DOI: 10.1109/TCDS.2017.2754143 Levinson [10] refers to this process as the human interaction environment, including social partners, in a way that facilitates engine: a set of capabilities including looking at objects of the acquisition of symbolic knowledge. Third, it needs to interest and interaction partners, pointing to these entities [11], actively maintain engagement with the social partners for a demonstrating curiosity as a desire to acquire knowledge [12] fluent interaction. Finally, the acquired symbols need to be and showing, telling and sharing this knowledge with others used in high-level cognitive functions dealing with linguistic [11], [13]. These are also coherent with the desiderata for communication and autobiographical memory. developmental cognitive architectures proposed in [14] stating In this section, we review related works on each of these that a cognitive architecture’s value system should manifest topics along with a brief overview of the solution adopted by both exploratory and social motives, reflecting the psychology the DAC-h3 architecture. of development defended by Piaget [15] and Vygotsky [16]. This interaction engine drives the robot to proactively control A. Functionally-driven vs. biologically-inspired approaches in its own acquisition and expression of knowledge, favoring the social robotics grounding of acquired symbols by learning multimodal repre- The methods used to conceive socially interactive robots sentations of entities through interaction with a human partner. derive predominantly from two approaches [17]. Functionally- In DAC-h3, an entity refers to an internal or external referent: designed approaches are based on reverse engineering methods, it can be either an object, an agent, an action, or a body part. assuming that a deep understanding of how the mind operates In turn, the acquired multimodal and linguistic representations is not a requirement for conceiving socially competent robots of entities are recruited in goal-oriented behavior and form the (e.g. [18], [19], [20]), whilst biologically-inspired robots are basis of a persistent concept of self through the development based on theories of natural and social sciences and expect two of an autobiographical memory and the expression of a verbal main advantages of constraining cognitive models by biological narrative. knowledge: to conceive robots that are more understandable We validate the proposed architecture following a human- to humans, as they reason using similar principles, and to robot interaction scenario where the robot has to learn concepts provide an efficient experimental benchmark from which the related to its own body and its vicinity in a proactive manner underlying theories of learning can be confronted, tested and and express those concepts in goal-oriented behavior. We show refined (e.g. [21], [22], [23]). One specific approach used a complete implementation running in real-time on the iCub hu- by Demiris and colleagues for the mirror neuron system is manoid robot. The interaction depends on the internal dynamics decomposing computational models implemented on robots of the architecture, the properties of the environment and the into brain operating principles which can then
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