Towards Learning by Interacting in Cognitive Systems, Christensen et al. Course: Robots Learning from Humans Kim, Sah-Moo SUALAB & Department of Mathematics Chung-Ang University

Contents Introduction Social Learning is Powerful! Ingredients for Social Learning : 1) Joint Attention Ingredients for Social Learning : 2) Interaction Management Conclusion 2

Introduction Why Learning by Interacting? What about former intelligence? Where is Social Learning? © 2015, SNU CSE Biointelligence Lab., 3 Learning by Interacting is an agreement that embodiment is a foundation for any kind of interactive learning Mostly, offline learning ☞ Learning ∩ Recognition = Empty!

Social Learning is Powerful! In Social Learning, particular information facilitates the learning process And increases its effectivity. An example on Social Learning? © 2015, SNU CSE Biointelligence Lab., 4 Observation on Parent-Infant model

Joint Attention “Perceptual Magnet Theory” Kuhl against the theory Question : How can joint attention help to learn things that an infant would not learn in a non-interactive situation? Synchrony and Acoustic packaging help to pay attention © 2015, SNU CSE Biointelligence Lab., 5

Modeling Joint Attention Mostly, Bottom-up On the other hand, purely model-driven joint- attention Multimodality again! © 2015, SNU CSE Biointelligence Lab., 6 Attentional processes need to able to take multi-modal information But synchronization and the handling of different processing rates are non-trivial

Interaction Management What’s Interaction Management? If it fails, then an awkward situation may happen! ‘Jiggle ‘ and ‘Jiggle-stop’ Contingent stimulation © 2015, SNU CSE Biointelligence Lab., 7

Modeling IM Bi-directional interaction Grounding process © 2015, SNU CSE Biointelligence Lab., 8 Not only focus on the same object with the partner, But also be able to exchange information about it Grounding is a mechanism that may serve as a general mechanism for learning higher-level linguistic interaction through non-linguistic, physical interaction

Pre-requisites for Modeling IM Ability to process multi-modal information in a way allowing to synchronize the information at different levels in order to draw conclusions about co-occurring events Possibility to develop top-down strategies from bottom-up data analysis Overall system has to be highly integrated © 2015, SNU CSE Biointelligence Lab., 9

Conclusion Learning should be modeled as a continuous process driven by social and interactive cues Complex perception-action system needs to be developed Remember 2 things : Joint Attention and Interaction Management © 2015, SNU CSE Biointelligence Lab., 10