Developmental Robotics and its Role Towards Artificial General Intelligence

Human intelligence develops through experience, robot intelligence is engineered – is it? At least in the mainstream approaches based on classical Artificial Intelligence (AI) and Machine Learning (ML) the robotic engineering approach is pursued and data- or knowledge-based algorithms are designed to improve a robot’s problem-solving performance. Based on this engineering perspective of classical AI/ML approaches plenty of valuable application-specific impact has been achieved. Yet, the achievements are often subject to restrictions that involve domain knowledge as well as constraints concerning application domains and computational hardware. Developmental Robotics seeks to extend this constrained perspective of engineered artificial robotic cognition by building on inspiration from biological, developmental processes to design robots that learn in an open-ended continuous fashion. Herein, Developmental Robotics seeks to investigate and model cognitively plausible inductive biases including curiosity, homeostasis and body schemas. This enables Developmental Robotics to consider cognitive domains that involve problem-solving, self-perception, developmental disorders and embodied cognition.

@Article{EWHN21, 
 	 author =  {Eppe, Manfred and Wermter, Stefan and Hafner, Verena Vanessa and Nagai, Yukie},  
 	 title = {Developmental Robotics and its Role Towards Artificial General Intelligence}, 
 	 journal = {KI - Künstliche Intelligenz},
 	 number = {35},
 	 volume = {},
 	 pages = {5-7},
 	 year = {2021},
 	 month = {Feb},
 	 publisher = {Springer},
 	 doi = {10.1007/s13218-021-00706-w}, 
 }