| Title | Interaction and Experience in Enactive Intelligence and Humanoid Robotics |
| Speaker | Prof. Chrystopher Nehaniv |
| Chair | Hiroki Sayama |
Abstract
We overview how sensorimotor experience can be operationalized for interaction scenarios in which humanoid robots acquire skills and linguistic behaviours via enacting a “form-of-life” in interaction games (following Wittgenstein) with humans. The radical enactive paradigm is introduced which provides a powerful framework for the construction of complex adaptive systems, based on interaction habit, and experience. Operationally, sensorimotor and internal variables and temporal extended flow of values over these provide raw information-theoretic sources serving as a uninterpreted experience in interaction with the physical and social environment that drive self-structuring of enactive intelligence. Enactive cognitive architectures (following insights of Varela, Thompson and Rosch) support social learning and robot ontogeny by harnessing information theoretic methods and raw uninterpreted sensorimotor experience to scaffold the acquisition of behaviours. The success criterion here is validation by the robot engaging in ongoing human-robot interaction with naive participants who, over the course of iterated interactions, shape the robot’s behavioural and linguistic development. Engagement in such interaction exhibiting aspects of purposeful, habitual recurring structure evidences the developed capability of the humanoid to enact language and interaction games as a successful participant. Examples from our lab illustrate application of these methods to achieve sensorimotor self-organization, ontogeny of socially contingent interaction and non-verbal behaviour switching in human-robot scenarios, as well as the acquisition of linguistic behaviours including development of a grounded, child-like two-word stage and forms of linguistic negation in interaction with human participants.
Biography
Professor Chrystopher L. Nehaniv is a Ukrainian-American mathematician and computer scientist. He received his BSc with honors from the University of Michigan, Ann Arbor in 1987, where he studied mathematics, biology, linguistics and cognitive science, and his PhD in Mathematics from the University of California at Berkeley in 1992. He has held academic and research positions in at Berkeley, Japan (professorship at University of Aizu, 1993-1998), and Hungary, and since 2001 is Research Professor of Mathematical and Evolutionary Computer Science at the University of Hertfordshire in the U.K, where he plays leading roles in the Algorithms, BioComputation, and Adaptive Systems Research Groups. He is author of over 200 publications and 30 edited volumes in computer science, mathematics, interactive systems, artificial intelligence, and systems biology, and is also coauthor of a monograph on algebraic theory of automata networks. Prof. Nehaniv is the Chair of the IEEE Computational Intelligence Society Task Force on Artificial Life and Complex Adaptive Systems, and associate editor of the journals Interaction Studies and BioSystems. He currently co-coordinates the EU FET Unconventional Computing project BIOMICS which explores the Biological and Mathematical basis of Interaction Computing (2012-2015). Prof. Nehaniv has contributed as co-PI in, among many other UK and EU grants, the EU funded Cogniron, RobotCub (producing the iCub humanoid), and ITALK projects which pioneered artificial intelligence for human-robot interaction and enactive developmental cogntiive architectures harnessing imitation and linguistic learning via contingent social interaction. His work brings novel mathematical approaches, especially computer algebraic automata theory (Krohn-Rhodes theory) and information-theoretic methods, to interactive and computationally intelligent systems of all kinds. His current research interests focus on interaction, development and enaction in biological and artificial systems, the notion of first and second-person experience (including phenomenological and temporally extended experience in ontogeny) in humanoids and living things, as well as on mathematical and computer algebraic foundations and methods for complex adaptive systems.
