scienceofintelligence.de

Admissions 2020
2020-01-14 08:30 - 2020-01-15 18:30 (Europe/Berlin)
Symposium and Interviews for prospective (post)doctoral researchers.

Guillermo Gallego (SCIoI): "Spatial AI and Event-based Vision"
2020-01-09 16:00 - 17:30 | FH 315, Fraunhoferstraße 33-36, Berlin, 10587
PI Lecture Series – “Spatial AI and Event-based Vision”
Prof. Dr. Guillermo Gallego
Robotic Interactive Perception Group, TU Berlin

Internal Models and Predictive Coding from a Robotics and Cognitive Science Perspective: Prof. Bruno Lara and Dr. Alejandra Ciria
2020-01-09 10:00 - 11:00 | MAR23 5.006, Marchstraße 23, Berlin, 10587, Germany
Prof. Bruno Lara (Cognitive Robotics, UAEM, Mexico) and Dr. Alejandra Ciria (Cognitive Psychology, UNAM, Mexico) will give a presentation on their research on internal models and predictive coding from a Robotics and Cognitive Science perspective. They are currently visiting researchers at the Adaptive Systems Group at HU Berlin with an Alexander-von-Humboldt Fellowship.
Abstract:
A cognitive system can be conceived as one which fulfills its goals anticipating the causes of its sensations by containing a predictive model of itself and its environment to select and guide action. During the last years, our research has focused on the issues of Internal Models, anticipation and multimodal representations within this framework. We have developed a number of systems that successfully make use of these concepts in the production of coherent behavior. Now, our main research interest is the study of predictions and how these can be learned by an agent taking into account the specific dynamics of its internal states. Special interest lays in the impact these dynamics bring into the learning capabilities and the interactions with the world of an agent. How does an artificial agent decide what is the relevant information to learn during its interactions with the world? Predicting future states accurately while seeking unanticipated novel states are competing pressures within an agent. We believe that these competing pressures should be resolved by tracking the prediction error dynamics of its internal states. An artificial agent endowed with this mechanism should be able to decide and plan its future actions in accordance with the proper type of novelty given its current knowledge and capabilities. Therefore, an artificial agent should be intrinsically motivated to select actions given its epistemic value providing the capability of open-ended learning.
Bruno Lara is a Professor at the Universidad Autónoma del Estado de Morelos (UAEM) and the Head of the Cognitive Robotics Lab at the Science Research Center at the UAEM since 2005. He holds a PhD in Mechatronics from King’s
College London. He did a postdoc in the TheoriLabor in the University of Jena, working on evolutionary robotics, and then a postdoc at the Max Planck Institute for Psychology Research in Munich, focusing on research on Cognitive
Robotics. In 2011, he spent a sabbatical stay in the Cognitive Robotics Lab at the Humboldt- Universitat zu Berlin. He is an Alexander von Humboldt Fellow.
His research interests include internal models, prediction, sensorimotor representations, and evolutionary robotics.
Alejandra Ciria is a postdoctoral researcher at the Humboldt-Universität zu Berlin, Department of Computer Science in the Adaptive Systems Group, Germany, Berlin (Alexander von Humboldt Foundation, Special Alumni Sponsorship, 2019).
She obtained a Master’s Degree in Cognitive Sciences in 2013 at the UAEM, Morelos, México.
She then studied a Ph.D. in Experimental Psychology at the Faculty of Psychology, UNAM, México, graduating in 2019.
Since 2011, she is an active member of the Cognitive Robotics Lab at the CInC-UAEM, México.
Her research focuses on computational modeling under the predictive processing framework, as well as the study of prediction error dynamics as a self-regulating mechanism.
Alejandra ́s research interests are centered in Psychophysics, Experimental Psychology, Cognitive Robotics, and Cognitive Sciences.

Adaptive Learning and Intelligent Tutor Systems: Rebecca Lazarides, Niels Pinkwart, Verena Hafner (SCIoI)
2019-12-19 10:00 - 11:00 | MAR23 5.006, Marchstraße 23, Berlin, 10587, Germany
Thursday Morning Lectures
Abstract: In educational psychology, the benefits and limitations of adaptive learning processes are currently under debate. In computer science, Intelligent Tutor Systems (ITS) exist that are adaptive to learners’ level of skills and knowledge, but it is an open research question how novel user modelling approaches and feedback strategies in ITS incorporating virtual agents can enhance positive emotions and motivation and reduce negative emotions in learning situations. This talk will provide an overview of current research questions in educational psychology about adaptive learning and new developments in the field of intelligent tutor systems.

Distinguished Lecture Series: William H. Warren (Brown University)
2019-12-12 16:00 - 17:30 | MAR23 4.064, Marchstraße 23, Berlin, 10587, Germany
Distinguished Lecture Series
On 12 December 2019, Professor William H. Warren (Brown University) will kick off the SCIoI Distinguished Lecture Series.
William Warren earned his undergraduate degree at Hampshire College (1976), his Ph.D. in Experimental Psychology from
the University of Connecticut (1982), did post-doctoral work at the University of Edinburgh, and has been a professor at Brown ever since.
My research focuses on the visual control of action – in particular, human locomotion and navigation.
On the one hand, I want to understand how motor behavior such as gait and other rhythmic movements are dynamically organized.
On the other, I seek to explain how such behavior is adaptively regulated by visual information in complex environments.
Using virtual reality techniques, my research team investigates problems such as the visual control of steering, obstacle avoidance,
pedestrian interactions, and collective crowd behavior.

Ingo Schulz-Schaeffer: Models As Epistemic Tools
2019-12-12 10:00 - 11:00 | MAR23 5.006, Marchstraße 23, Berlin, 10587, Germany
Thursday Morning Lectures

Marianne Maertens (SCIoI): “How We Perceive Surfaces”
2019-12-05 16:00 - 17:30 | FH 315, Fraunhoferstraße 33-36, Berlin, 10587
PI Lecture Series
Marianne Maertens: “How we perceive surfaces”

Surjo R. Soekadar (Charité - University Medicine Berlin): Brain/Neural-Machine Interfaces for Assistance and Beyond
2019-12-05 10:00 - 11:30 | MAR23 5.006, Marchstraße 23, Berlin, 10587, Germany
Thursday Morning Lectures
Abstract:
Implementation of neural control in the application of advanced robotic systems promises restoration of autonomy and quality of life in severe paralysis. Moreover, neurotechnologies that are capable of analyzing, interpreting and modulating brain activity in real-time promise to advance our understanding of the underlying mechanisms of human brain functions. But what are the current challenges and perspectives for brain-computer interfaces (BCI)? And how can neurotechnologies improve health and quality of life? This talk will provide an overview of the current state-of-art in clinical BCI applications and introduce the newest developments in the field. Besides sketching technological boundaries, also neuroethical dimension will be discussed.
Bio: Surjo R. Soekadar, MD, is Einstein Professor of Clinical Neurotechnology at the Charité – University Medicine Berlin. From 2009-2011, he was fellow at the Human Cortical Physiology and Stroke Neurorehabilititation Section (HCPS) at the NIH, USA. After his return to Germany, he became head of the Applied Neurotechnology Lab at the University Hospital of Tübingen, where he also served as senior consultant in the Dept. of Psychiatry and Psychotherapy. His research interests include cortical plasticity in the context of brain/neural-machine interface (B/NMI) applications, non-invasive brain stimulation and neural mechanisms of learning and memory.

Stephen Cave: Intelligence as Ideology: From IQ to AI
2019-11-29 15:00 - 16:30 | MAR23 5.006, Marchstraße 23, Berlin, 10587, Germany
A Thursday Talk on a Friday!
Dr Stephen Cave is Executive Director of the Leverhulme Centre for the Future of Intelligence
and Senior Research Associate in Philosophy at the University of Cambridge
He earned his PhD in philosophy from Cambridge, then spent a decade in the British Foreign Office, where he served as a policy advisor and diplomat.
He is author of the book Immortality (Penguin Random House), a New Scientist book of the year, and co-editor of the forthcoming AI
Narratives: A History of Imaginative Thinking About Intelligent Machines (OUP). His cross-disciplinary research interests currently focus on the nature, portrayal and governance of AI.
Abstract:
The notion of intelligence has always been political, in that is has been used consistently to establish and enforce systems of social dominance.
This talk will begin with a historical overview of this, from Aristotle to IQ, showing the role that assessment of intelligence has played in establishing hierarchies
including patriarchy and colonialism. It will then ask what this legacy means in the age of intelligent machines, arguing that this history is distorting the
current debate about the ethics and impact of AI. In particular, it will examine the focus on automation and middle-class jobs, the cult of brilliance in the
technology sector, and the fear of artificial super-intelligence.
http://lcfi.ac.uk/team/stephen-cave/

Matt Crosby (Imperial Collge London): Kinds of Intelligence: Testing AI on Animal Cognition Tasks
2019-11-28 10:00 - 11:30 | MAR23 5.006, Marchstraße 23, Berlin, 10587, Germany
Thursday morning lectures
ABSTRACT: I will give a brief overview of the ongoing work of the Kinds of Intelligence team at the Leverhulme Centre for the Future of Intelligence and then focus on the Animal-AI project. Our aim is to bring insights from comparative cognition to the AI community and facilitate work towards more general, and cognitively-inspired, kinds of intelligence. To this end we recently ran the Animal-AI Olympics competition. Participants were given a small simulated arena with simple physics and a few basic objects to interact with. Their goal was to submit a robust food retrieval agent. The only information they had about the tests were that they were constructed in the arena out of known items, required the retrieval of designated food objects, and were based on tests passed by animals. We also provided a syllabus of capabilities required to solve our testbed including navigation, spatial memory, object permanence, and simple causal reasoning. Now that the competition has finished, we can reveal our testbed and present it as an open challenge for AI. I will also present our plans to extend the environment and eventually move the paradigm from simulation to the real world.
BIO: Matthew Crosby is a postdoctoral researcher on the Kinds of Intelligence project at the Leverhulme Centre for the Future of Intelligence. He is based at Imperial College London where he works with Murray Shanahan on the broad area of artificial cognition. He has an interdisciplinary background spanning AI, robotics, cognitive science, and philosophy of mind and is interested in modern AI approaches that span this range of disciplines. His long-term goal is to better understand what it means to ‘have a mind’ by knowing how to build an artificial system that has one.

Jörg Raisch (SCIoI): Models for Feedback - Costs and Benefits of Simplicity
2019-11-21 16:00 - 17:30 | FH 315, Fraunhoferstraße 33-36, Berlin, 10587
PI Lecture Series
Models for Feedback — Cost and Benefits of Simplicity
Joerg Raisch, Control Systems Group, TU Berlin
Abstract:
We’ll start with a short introduction to feedback control. I’ll
emphasise that the systematic design of feedback requires a formal
model of the system to be controlled, and that the choice of such a
model represents a fundamental degree of freedom in the design
process. In general, one is interested in “simple” models, where the
notion of “simplicity” may refer to the dimension or the structure
(e.g., linearity) of the model. We’ll explore possible costs that are
related to model simplification: examples are the loss of predictive
power or a weaker algebraic setting. We will finally discuss
conditions that make these costs acceptable.

Iyad Rahwan (MPIB): How To Trust a Machine
2019-11-21 10:00 - 11:30 | MAR23 5.006, Marchstraße 23, Berlin, 10587, Germany
Thursday morning lectures
Talk by Iyad Rahwan, director at the Max Planck Institute for Human Development and Associate Professor at the MIT Media Lab.
The topic of his talk will be “How to Trust a Machine”.

Lange Nacht der Wissenschaften 2019
2019-06-15 10:00 - 21:00
Robots playing soccer, lab mice, visual experiments: SCIoI members demonstrated their science and talk about their discoveries for an entire evening.
