Children acquire language by interacting with their caregivers and others in their social environment. When children start to talk, their sensory-motor intelligence (visual perception, body movement, navigation, object manipulation, auditory perception and articulatory control) is already reaching a high level of competence. Importantly, communication is based on representations and skills that have started to develop much earlier and that are shaped already in first (social) interactions. These interactions are multimodal in nature and vary across contexts. The contexts vary not only across developmental time and situations within individuals, but also between individuals, socio-economic groups and cultures. Continuously, representations become further enriched in ongoing interactions and across different contexts.
Even though there are various efforts in developmental robotics to model communication, the emergence of symbolic communication is still an unsolved problem. We are still lacking convincing theories and implementations that show how cooperation and interaction skills could emerge in long-term experiments with populations of robotic agents or how these skills develop in children. Importantly, the continuous acquisition of knowledge in different contexts and being able to further enrich the underlying representations provides a potential powerful mechanism (cross-situational learning), which is already well recognized in learning in children. Still, we need to know more about how children recognize contexts and how their language learning benefits from different language use varying across contexts.
This special issue aims at surveying the state of the art of the emergence of communication which requires combining and integrating knowledge from diverse disciplines: developmental psychology, robotics, artificial language evolution, complex systems science, computational linguistics and machine learning. Topics relevant to this special issue include, but are not limited to
· Psychological experiments on language learning in children
· Corpus-based approaches to language acquisition
· Language learning models for all stages of acquisition (gesture learning, early lexicon and grammar)
· Representations for language learning (sensorimotor schemas, constructions, neural networks, mirror neurons)
· Cognitive architectures and strategies for language learning
· Cross-situational learning
· Language acquisition and development of self-awareness
· Role of context in language learning
· Role of embodiment in language learning
· Role of multimodality (gesture, gaze etc) in language learning
· Role of social interaction and joint attention
· Co-development of skills, e.g. motor and language skills; integration of natural language grounding into perception-action cycles
· Connection with cultural and biological evolution of language
Manuscripts should be prepared according to the “Information for Authors” of the journal found at http://cis.ieee.org/publications.html and submissions should be done through the IEEE TCDS Manuscript center: https://mc.manuscriptcentral.com/tcds-ieee and please select the category “SI: Multi-Modal Integration and Development”.
31.October 2017 – Deadline for manuscript submissions
15.December 2017 – Notification of authors
15. January 2018 – Deadline for submission of revised manuscripts
February/March 2018 – Final decisions
March/April 2018 – Special Issue Publication in IEEE TCDS
Chen Yu (Indiana University, USA)
Katharina J. Rohlfing (Paderborn University, Germany)
Malte Schilling (CITEC Bielefeld, Germany)
Michael Spranger (Sony Computer Science Laboratories Inc, Japan)
Paul Vogt (Tilburg University, the Netherlands)
Malte Schilling: schilli at techfak dot uni-bielefeld dot de
Michael Spranger: michael dot spranger at gmail dot com