[visionlist] New "Developing Minds" global online lecture series; September 30: Pierre-Yves Oudeyer
triesch at fias.uni-frankfurt.de
Sun Sep 19 01:37:36 -04 2021
What: New bi-monthly "Developing Minds" global online lecture series; inaugural lecture by Pierre-Yves Oudeyer, INRIA, Bordeaux Sud-Ouest, France on "Developmental AI: machines that learn like children and help children learn better"
When: Thursday, September 30, 13:00 UTC
Where: online via zoom; please register at: https://sites.google.com/view/developing-minds-series
In 1950, Alan Turing asked "Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's?" Today, over 70 years later, constructing a computer program that can learn like a child and that develops a human-like general intelligence is still considered a grand, if not the ultimate, challenge for artificial intelligence (AI). An interdisciplinary community of scientists from AI, Cognitive Science, Psychology, Engineering, and Neuroscience are tackling this grand challenge. In the Developing Minds global lecture series we showcase the progress being made. It is organized by the IEEE Technical Committee on Cognitive and Developmental Systems of the IEEE Computational Intelligence Society.
The inaugural lecture by Pierre-Yves Oudeyer is entitled: "Developmental AI: machines that learn like children and help children learn better"
Current approaches to AI and machine learning are still fundamentally limited in comparison with the amazing learning capabilities of children. What is remarkable is not that some children become world champions in certains games or specialties: it is rather their autonomy, open-endedness, flexibility and efficiency at learning many everyday skills under strongly limited resources of time, computation and energy. And they do not need the intervention of an engineer for each new task (e.g. they do not need someone to provide a new task specific reward function or representation).
I will present a research program, which I call Developmental AI, that studies models of open-ended development and learning. These models are used as tools to help us understand better how children learn, as well as to build machines that learn like children with applications in educational technologies, automated discovery, robotics and human-computer interaction. I will ground this research program into several fundamental ideas proposed by developmental psychologists:
1) the child is autotelic, setting its own goals and spontaneously exploring the world like a curious little scientist (e.g. Piaget, Berlyne);
2) intelligence develops in a social context, where language and culture are internalized to become cognitive tools (e.g. Vygostky and Bruner);
3) intelligence is embodied and develops through self-organization of the dynamical system formed by the brain-body-environment interactions (e.g. Thelen and Smith).
I will show how, together with many colleagues and students, we have worked on operationalizing these ideas in computer and robotic models, and explain how this has enabled to advance child development understanding, open new possibilities for AI systems (including for recent language-guided intrinsically motivated Deep RL systems and for training more classical Deep RL systems to foster generalization), and led to applications now used by thousands of children in the world to help them learn (educational technologies).
Dr. Pierre-Yves Oudeyer has been Research Director at Inria, France, and head of the Flowers lab (Inria, Univ. Bordeaux, Ensta ParisTech). Before, he has been a permanent researcher in Sony Computer Science Laboratory for 8 years (1999-2007). He studies models of open-ended development and learning, at the frontiers of AI and cognitive sciences. These models are used as tools to help us understand better how children learn, as well as to build machines that learn like children within the field of developmental artificial intelligence. He has been developing models of intrinsically motivated learning, pioneering curiosity-driven learning algorithms working in real world robots, and developed theoretical frameworks to understand better human curiosity and autonomous learning. He also studied mechanisms enabling machines and humans to discover, invent, learn and evolve language. He is also working on applications in educational technologies, automated discovery, video games, robotics and human-computer interaction. He received several prizes for his work in developmental AI and on the origins of language. In particular, he is laureate of the Inria-National Academy of Science young researcher prize in computer sciences, and of an ERC Starting Grant EXPLORERS. Finally, he is also working actively for the diffusion of science towards the general public, through the writing of popular science articles and participation to radio and TV programs as well as science exhibitions.
Web: http://www.pyoudeyer.com and http://flowers.inria.fr
Linda B. Smith, Indiana University
Joshua B. Tenenbaum, MIT
Please visit https://sites.google.com/view/developing-minds-series/home for up-to-date information.
Prof. Dr. Jochen Triesch
Johanna Quandt Research Professor
Frankfurt Institute for Advanced Studies
Tel: +49 (0)69 798-47531
Fax: +49 (0)69 798-47611
More information about the visionlist