Dear colleagues, we are happy to announce the release of the latest issue of the IEEE CIS Newsletter on Cognitive and Developmental Systems (open access). This is an annual newsletter addressing the sciences of developmental and cognitive processes in natural and artificial organisms, from humans to robots, at the crossroads of cognitive science, developmental psychology, artificial intelligence, machine learning and neuroscience. It is available at: https://tiny.cc/2072iz <https://tiny.cc/2072iz> Featuring dialog: === "Leveraging Adaptive Games to Learn How to Help Children Learn Effectively" == Dialog initiated by Georges Kachergis with responses from: Jennifer Zosh, Roberta Golinkoff, Kathy Hirsch-Pasek, Rebecca Dore, Brenna Hassinger-Das, Benedict du Boulay and Ken Koedinger. == Topic: Fundamental research aiming to understand better how children learn and develop can have a major societal impact. One key example is education: in the last decades, several advances enabled to show how certain learning and teaching techniques could improve significantly comprehension and memorization in children. A major challenge consists in translating these advances into real classroom practices, a challenge at the core of “translational educational sciences”. In this newsletter, a dialog initiated by Georges Kachergis highlights how adaptive learning technologies, e.g. educational apps, can be both an efficient channel for this translation, and an opportunity for further understanding how to foster efficient learning in the class- room. Several experts of this domain provide their point of view and discuss various challenges to be addressed, ranging from establishing strong collaborations between developmentalists, app developers and teachers, to deploying large-scale ecologically valid experimentations. They also offer a perspective on how artificial intelligence can play a key role in impactful educational apps, enabling to implement per- sonalized and motivating learning strategies. Call for new dialog: === «How to Evaluate Open-ended Learning Agents? » == Dialog initiated by Clément Moulin-Frier == Topic: Then, a new dialog initiation is proposed by Clément Moulin-Frier on a fundamental question for the future of AI: How to evaluate open-ended learning agents? While impressive progress was made recently in reinforcement learning, as shown by performance in benchmarks with a set of pre-defined external objectives, a major challenge is now to build autonomous agents that can progressively discover and learn open repertoires of skills in open worlds. Several steps in this direction have been made in the last decade, such as algorithms enabling agents to imagine their own goals and self-organize their learning curriculum (initially in the CDS community, and recently extended in the machine learning community). Another related line of work is open-ended evolution in multi-agent systems with co-evolution. However, a key challenge is how to measure progress in this area, as traditional RL benchmarks were not constructed to address open-ended learning. I invite all readers interested to participate to this dialog to send me their response by June 30th, 2020. The length of each response must be between 600 and 800 words including references (contact pierre-yves.oudeyer@inria.fr <mailto:pierre-yves.oudeyer@inria.fr>). Let us remind you that all issues of the newsletter are all open-access and available at: https://goo.gl/ZjjZNz <https://goo.gl/ZjjZNz> I wish you a stimulating reading! Best regards, Pierre-Yves Oudeyer, Editor of the IEEE CIS Newsletter on Cognitive and Developmental Systems Research director, Inria Head of Flowers project-team Inria, Univ. Bordeaux and Ensta ParisTech, France http://www.pyoudeyer.com <http://www.pyoudeyer.com/> Twitter: https://twitter.com/pyoudeyer <https://twitter.com/pyoudeyer> and Fabien Benureau, Editorial Assistant Cognitive NeuroRobotics Unit, Okinawa Institute of Science and Technology 1919-1 Tancha, Onna, Okinawa Japan http://fabien.benureau.com <http://fabien.benureau.com/> Email: fabien.benureau [at] oist [dot] jp