Development of Compositionality through Interactive Learning of Language and Action of Robots Using Free Energy Principle - Prof. Dr. Jun Tani - University of Hamburg
The focus of my research has been to investigate how cognitive agents can develop structural representation and functions via iterative interaction with the world, exercising agency and learning from resultant perceptual experience. For this purpose, my team has developed various models analogous to predictive coding and active inference frameworks based on the free energy principle. Those models have been used for conducting diverse robotics experiments which include goal-directed planning and replanning in a dynamic environment, social embodied interactions, development of the higher cognitive competency for meta-cognition. The current talk highlights a set of emergent phenomena which we observed in our recent robotics study focused on embodied language [1]. These findings could inform us how children can develop compositional linguistic competency only through limited amount of sensory-motor-language associative learning.
Reference:
[1] P. Vijayaraghavan, J. Queißer, S. Flores, J. Tani, (2025). Development of compositionality through interactive learning of language and action of robots. Science Robotics, 10, eadp075.
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