scienceofintelligence.de

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

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”.

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.

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.

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/

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.

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”

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

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.

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.

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.

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

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

Wissenschaft im Sauriersaal - Lecture by Prof. Jens Krause (SCIoI) (in German)
2020-01-17 19:30 - 20:30 | Naturkundemuseum
On SCIoI faculty member Professor Jens Krause will open this year’s lecture series with a talk on swarm intelligence:

“Ob Mensch oder Tier: Warum der Schwarm intelligenter ist als der Einzelne”.
The lecture is in German.
Link to event page here
Photo by: Rodrigo Friscione Wyssmann

Salon Sophie Charlotte 2020 - Talk with Miriam Kyselo: Wie kommt die Welt in meinem Kopf? (in German)
2020-01-18 20:00 - 21:00
SCIoI faculty member Miriam Kyselo and philosopher Joerg Fingerhut (Einstein Group „Consciousness, Emotions, Values“) take part in a discussion chaired by Andreas Sentker (the ZEIT-Wissen chief editor) about the role of the brain and the body, but also of cultural artifacts, in the creation of the world. The talk (in German) is part of the Salon Sophie Charlotte 2020 (https://salon.bbaw.de/home/programm/raum-327/)

Alex Kacelnik (University of Oxford): What Are Minds for, and How Do They Work?
2020-01-23 16:00 - 17:30 | MAR23 4.064, Marchstraße 23, Berlin, 10587, Germany
PI Lecture Series
Abstract:
The biological perspective on intelligence is well represented by the following quotes: “Is it not reasonable to anticipate that our understanding
of the human mind would be aided greatly by knowing the purpose for which it was designed?” (George Williams) and “Everybody is a genius.
But if you judge a fish by its ability to climb trees, it will live its whole life believing that it is stupid” (Albert Einstein).
Meanwhile, those working on synthetic approaches to intelligence are often inspired by Richard Feynman’s claim that “What I cannot create, I do not understand”.
These quotes embody useful and inspiring questions for research on intelligence: why does it evolve, how specific is it, and to what extent can theoretical models
that we create behave intelligently. I will describe studies of animal intelligent behaviour and our attempts to understand it.

Alex Kacelnik FRS is a behavioural ecologist that works on animal behaviour and its underlying psychological mechanisms.
His research includes studies of decision making, learning and memory in birds, mammals, insects and other animals.
In SCioI he collaborates with Oliver Brock and Alice Auersperg in research on intelligence in cockatoos and its emulation in artificial systems.
He is also is a member and promotor of the Oxford-Berlin partnership.

John-Dylan Haynes (SCIoI): “What Can Neuroimaging Tell Us About Human Intelligence?”
2020-02-06 16:00 - 17:30 | MAR23 4.064, Marchstraße 23, Berlin, 10587, Germany
The concept of intelligence in cognitive science has been highly elusive. One pragmatic approach to understanding intelligence is to use classical intelligence tests, such as the Wechsler Adult Intelligence Scale (WAIS). In such tests, performance is assessed in a number of specific subtask items, and the performance across these items is then integrated to an overall (or “full scale”) IQ. Neuroimaging has contributed to both the single-item and the full-scale performance. At the item level, several studies have looked at resource and efficiency models. At the full-scale level studies have looked at overall brain structure, as well as the importance of various subregions of the brain. Furthermore, various architectural principles can be considered. Overall, this line of research contributes to the understanding of intelligent cognition in a specific biological substrate, the healthy human brain.
Prof. John-Dylan Haynes
Charité – Universitätsmedizin Berlin, HU Berlin, Psychology

Henry Shevlin, Leverhulme Centre for the Future of Intelligence: General Intelligence: An Ecumenical Heuristic for Artificial Consciousness Research?
2020-02-13 16:00 - 17:30 | MAR23 4.064, Marchstraße 23, Berlin, 10587, Germany
Henry Shevlin is a research associate at the Leverhulme Centre for the Future of Intelligence (Cambridge).
He did his PhD at CUNY Graduate Center in New York with a thesis on “Consciousness, Perception and Short-Term Memory”.
Link to CV here
ABSTRACT:
The science of consciousness has made great strides in recent decades, both in the development of theoretical frameworks and in the refinement of our experimental and clinical tools for the assessment of consciousness in humans. However, the proliferation of competing theories makes it harder to reach consensus about artificial consciousness. While for purely scientific purposes we might wish to adopt a ‘wait and see’ attitude, we may soon face practical and ethical questions about whether, for example, an artificial agent is capable of suffering. Moreover, many of the methods used for assessing consciousness in humans and even non-human animals are not straightforwardly applicable to artificial systems. With these challenges in mind, I propose that we adopt an ecumenical heuristic for artificial consciousness so that we can make tentative assessments of the likelihood of consciousness arising in different artificial systems. I argue that such a heuristic should have three main features: it should be intuitively plausible, theoretically neutral, and scientifically tractable. I claim that the concept of general intelligence – understood as a capacity for robust, flexible, and integrated cognition and behaviour – satisfies these criteria and may thus provide the basis for such a heuristic, allowing us to make initial cautious estimations of which artificial systems are most likely to be conscious.
Lecture hosted by: Miriam Kyselo

Career Day for Doctoral Candidates 2020 - Berlin University Alliance
2020-02-18 09:00 - 17:30 | Humboldt Universität, Luisenstr. 56, 10117 Berlin
Career Day for Doctoral Researchers 2020, Bildquelle: Carolina Valsecchi Gillmeister
On February 18, 2020 the Humboldt-Universität zu Berlin will host the next career day for doctoral candidates.
The event is organized by doctoral researchers from Humboldt-Universität, Freie Universität and Charité-Universitätsmedizin Berlin and supported by
the members of the Berlin University Alliance and HEIBRiDS, the Helmholtz Einstein International Berlin Research School in Data Science. In a mix of
presentations and World Cafés speakers from varied sectors and walks of life will give insights in their careers and answer questions of the participants.
Click here for more info and registration.

“The Ethics of AI-Chemy – When Science Meets Hype” – Keynote Lecture by Prof. Dr. Oliver Brock
2020-02-19 17:30 - 19:00 | HU Berlin – Institut für Biologie, Phillipstraße 12/13a, Berlin, Berlin, 10115, Germany
Winter School Keynote Lecture: Oliver Brock (Cluster Science of Intelligence, TU Berlin)
Cluster Speaker Prof. Dr. Oliver Brock will deliver the keynote lecture at this year’s Winter School Ethics and Neuroscience.

The 9th Winter School “Ethics and Neuroscience is organized by the BCCN Berlin/ICCN and the Berlin School of Mind and Brain.
The event is tailored for MSc and PhD students, but covers a range of topics of potential interest to other researchers, reflecting
on the ethical and societal consequences of modern neuroscience.

Theoretical foundations, as well as practical and ethical aspects are addressed. Participants will benefit from a combination of lectures with
group work and discussions, where they will put the learned content into practice.
Read more here

Venue:Humboldt-Universität zu Berlin
Institut für Biologie, Campus Nord, House 2, Lecture Hall 1
Entry to Campus from: Luisenstraße 56, 10117 Berlin
Entry to Campus from: Philippstraße 12/13a, 10115 Berlin
Contact: Dr. Dirk Mende, Berlin School of Mind and Brain
030 / 2093-89768

Pascal Klink (TU Darmstadt): Self-Paced Reinforcement Learning
2020-02-20 10:00 - 11:00 | MAR23 4.064, Marchstraße 23, Berlin, 10587, Germany
Thursday Morning Lectures
Abstract:
Generalization and adaptation of learned skills to novel situations is a core requirement for intelligent autonomous robots. Although contextual reinforcement learning provides a principled framework for learning and generalization of behaviors across related tasks, it generally relies on uninformed sampling of environments from an unknown, uncontrolled context distribution, thus missing the benefits of structured, sequential learning. We introduce a novel relative entropy reinforcement learning algorithm that gives the agent the freedom to control the intermediate task distribution, allowing for its gradual progression towards the target context distribution. Empirical evaluation shows that the proposed curriculum learning scheme drastically improves sample efficiency and enables learning in scenarios with both broad and sharp target context distributions in which classical approaches perform sub-optimally.

Bio:
Pascal is a Ph.D. student at the Intelligent Autonomous Systems (IAS) Group at TU Darmstadt. At IAS, he works for the ROBOLEAP project, where he develops methods for reinforcement learning in unstructured, partially observable real world environments. Before starting his PhD, Pascal completed his Bachelor’s degree in Computer Science and Master’s degree in Autonomous Systems at the TU Darmstadt. Within his Master’s thesis he worked on “Generalization and Transferability in Reinforcement Learning” and was supervised by Hany Abdulsamad, Boris Belousov and Jan Peters

Prof. Katja Liebal (FU Berlin): Understanding the Human Mind: The Value of a Comparative Perspective
2020-02-27 10:00 - 11:00 | SCIoI, MAR Building, Marchstr. 23, Berlin
Abstract: Are humans unique? If so, which cognitive and communication skills characterize human beings? Are these characteristics universal, or do they vary depending on the individual’s social, ecological, and cultural background? While it may sound plausible that answering these questions requires the comparison of different cultural groups to learn about the universals and variability of human behavior, it seems much less convincing that we can also benefit from studying other species, especially when our interest centers on the psychology of the human being. However, I argue that, when aiming to understand human psychology, we benefit from a frame of reference against which to assess it. The comparison with the psychology of other animals, and nonhuman primates in particular, can provide such a frame of reference and thereby contribute to the extraction of the definitive characteristics of the human species.

Bio: Katja Liebal is a comparative psychologist with a background in biology. After finishing her PhD on social communication of great apes at the Max Planck Institute for Evolutionary Anthropology in Leipzig, she has worked as lecturer at the Department of Psychology at the University of Portsmouth, UK, and as Assistant Professor for Evolutionary Psychology at the Cluster Languages of Emotion at Universität Berlin. Currently, she works as Professor for Comparative Developmental Psychology at the Psychology department at Freie Universität Berlin. Her main research interests center on the multimodal communication of nonhuman primates and human children and the developmental trajectories of their corresponding socio-cognitive and communicative skills. Furthermore, she is interested in the prosocial behavior of great apes and children from diverse cultural backgrounds. She uses observational and experimental methods and combines cross-species, cross-cultural approaches to study different species of great apes and human children from different cultural contexts.

Pia Bideau and Raphael Deimel: Boost Your Experiments!
2020-03-05 10:00 - 11:00 | SCIoI, MAR Building, Marchstr. 23, Berlin
“Boost your experiments!”
The ScioI cluster provides for several post-doc level research positions for improving scientific integration across disciplines, as well as for
advancing the level of sophistication in experiments we can conduct in the ScioI Labs. Currently, there are two “support” post-docs, Pia Bideau and Raphael Deimel. Pia is an expert in motion-based image segmentation and rooted in Computer Vision, whereas Raphael is rooted in Robotics and has recently worked on models of mechanical behavior and human-robot interaction. In this talk, both will give an overview on their respective skills and prior work with the primary aim to inform fellow researchers on systems and hardware available to implement unique experiments in current and future projects.

Marianne Maertens & Martin Rolfs (SCIoI): Paradigm Shift in Vision Science and Maybe Other Disciplines?
2020-03-19 10:00 - 11:00 | SCIoI, MAR Building, Marchstr. 23, Berlin
Abstract:
Implicit or explicit assumptions which used to guide our empirical study of visual perception have started to be called into question. We would like to share this observation with other people, hear about similar or different developments in other fields, and discuss its consequences.

Zoom Talk: Dimitri Coelho Mollo (SCIoI): Introducing the Seminar “Philosophy of Artificial Intelligence”
2020-04-02 10:00 - 11:00 | On ZOOM (Contact us for Link)
Thursday Morning Talk
SCIoI postdoctoral researcher Dimitri Coelho Mollo will be giving us a sneak peak of his upcoming seminar for the SS2020 “Philosophy of Artificial Intelligence” and present his current work on the project “Concept of Intelligence” (PIs: Michael Pauen, Miriam Kyselo, John-Dylan Haynes).

Zoom Talk: Ralf Kurvers (MPI): How To Sway Voters
2020-04-16 10:00 - 11:00 | On ZOOM (Contact us for Link)
Thursday morning talk

How to sway voters
Across the world, politicians challenging the established elite are rising. Presenting contrarian views with high confidence, these politicians challenge the status quo, calling for a radically different course of action, often going against scientific evidence. Systematic investigations of the success of such ‘contrarian’ strategies are, however, absent. Though the process of advice taking is well-studied, the equally-important process of advice-giving has received much less attention. We present a systematic investigation of the success of the ‘contrarian’ in attracting the attention of decision-makers. Using game-theoretical modeling, we find that a contrarian strategy is a Nash equilibrium. Next, we tested whether this contrarian strategy is successful in drawing the attention of decision-makers across seven experiments testing over 800 participants. We found that, across all experiments, participants are more likely to follow the ‘contrarian’ than an advisor who honestly communicates the available evidence. This was found for participants who made decisions by themselves, in anonymous groups in which decisions were pooled using a majority vote, as well as in communicating groups. The success of the contrarian increased the more unpredictable the environment was. Our results show that actively going against the evidence is a powerful strategy to attract followers, and this explains the recent (and historical) success of such contrarian leaders. Especially in highly uncertain situations, as for example the recent Corona outbreak, such strategies are successful.

Zoom Lecture: Fatma Deniz (UC Berkeley & TU Berlin): Natural Language Representations in the Human Brain
2020-04-23 10:00 - 11:00 | On ZOOM (Contact us for Link)
Thursday Morning Lectures (on Zoom)
Natural Language Representations in the Human Brain

Abstract
An integral part of human language is the capacity to extract the meaning of words through different sensory modalities. For example, humans can easily comprehend the meaning of language presented through auditory speech or written text. However, how the human brain represents language in different modalities is still unclear. I suggest to observe the human brain performing tasks in its most natural setting, then build predictive models of brain responses, and create generalizable and reproducible results that aim to help in unifying our understanding of how the human brain processes linguistic information. In my talk, I will present predictive models of brain responses collected using functional magnetic resonance imaging while human participants listened to or read natural narrative stories. Using natural text and vector representations derived from natural language processing methods I will first present a modeling framework to study language processing in the human brain across modalities. I will then discuss how contextual effects modulate the representation of word meaning in the human brain. I will end my talk with research directions on how different languages are represented in the brains of bilinguals and how we could use the knowledge learned from the brain to augment the design of natural language processing algorithms.
Bio:
Fatma Deniz is the team leader and co-PI of a US-German collaborative research project and holds joint affiliations between Technical University Berlin and University of California, Berkeley. Prior to that, she was a postdoctoral fellow in Dr. Jack Gallant’s laboratory at UC Berkeley, a Moore-Sloan Data Science Fellow at Berkeley Institute for Data Science and a fellow at the International Computer Science Institute in Berkeley. In her work, Dr. Deniz uses machine-learning approaches and large-scale brain data to understand how language is represented in the brain. Dr. Deniz received her Ph.D. from the Computer Science Department at Technical University Berlin and was a member of Haynes Neuroimaging Lab led by Dr. John-Dylan Haynes at BCCN Berlin. She received her bachelor’s and master’s degrees in Computer Science from the Technical University Munich and worked with Dr. Christof Koch at Caltech. Dr. Deniz is an advocate of reproducible research practices and is an editor of the book “The Practice of Reproducible Research”.

Photo by Robina Weermeijer on Unsplash

Martin Rolfs (SCIoI): The Impact of Visual Actions on Human Vision
2020-04-23 16:00 - 17:30 | On ZOOM (Contact us for Link)
PI Lecture on Zoom
The impact of visual actions on human vision
More than 10,000 times every waking hour, we use rapid movements of our eyes, head and body to reorient our gaze. These visual actions allow us to see every aspect of the visual world at the highest resolution. It seems likely — in particular within SCIoI — that we can only begin to understand perception and cognition if we study their fundamental mechanisms in active observers. Yet psychology and neuroscience have long studied vision and motor control largely independently, presenting two success stories: Vision has been the work horse of perception research for more than a century and the brain circuits controlling gaze movements are now among the best understood in systems neuroscience.
It is at the intersection of these two systems, however, that we encounter the most intriguing questions. How do we not experience the brisk motion of the entire scene on the retina every time the eyes move? How does the visual system keep track of objects’ changing retinal locations across consecutive glances. And how do we routinely attribute retinal motion to our own movements rather than to motion in the world. To explain these phenomena, research and theories across disciplines have focused on how the brain uses its knowledge about ongoing movement plans to predict and compensate for undesirable side effects of visual actions. I will present a number of findings from psychophysical studies that, more often than not, give more surprising answers and that raise new questions about the tight weaving of perception and action.

Zoom Lecture: Oliver Brock, Verena Hafner, Pawel Romanczuk (SCIoI): The Role of Example Behaviors in Science of Intelligence and for Your Project
2020-04-30 10:00 - 11:00 | On ZOOM (Contact us for Link)
Thursday Morning Talk (on Zoom)
Abstract:
One of the assumptions made in the original SCIoI proposal is that intelligence is non-decomposable. This means that intelligent behavior results to a large degree from the interactions between component and not only from the components themselves. Components have different names, depending on what discipline you are from. If you look at the study of cognition, you might call these components “attention, the formation of knowledge, memory and working memory, judgment and evaluation, reasoning and “computation”, problem solving and decision making, comprehension and production of language” [Wikipedia]. To be able to study the interactions among such components, SCIoI has proposed three Example Behaviors, each associated with a different “type” of intelligence:
1) Escaping from an escape room – individual intelligence
2) Learning in social interaction – social intelligence
3) Cooperative shepherding – collective intelligence
These example behaviors integrate the synthetic output of SCIoI projects, mostly from research unit 1, but indirectly also from RU2 and RU3. The idea is the following: If you develop an intelligence mechanism for visual attention, this mechanism should demonstrate its validity in the context of an integrated “intelligent” system. Only then can we study and understand the interactions among your and other components. We will therefore integrate your mechanism into one of the three example platforms, one platform for each example behavior. Within this system, the interactions with other components are revealed and we can observe your component’s functionality within their context.
This presentation will trigger a SCIoI-wide, gradual process of building the three example behaviors. The goals of the presentation are:

to briefly talk about non-decomposability
to discuss how example behaviors fundamentally contribute to SCIoI
to introduce the three example platforms (mobile manipulator for behavior 1, humanoid robots for behavior 2, and swarm robots for behavior 3), including sensors, actuators, possible interfaces and uses
to provide you with initial information that should enable you to start thinking about the integration of your contribution into the platform(s)
to answer your questions to plan next steps(Photo by Brett Jordan on Unsplash)

Zoom Talk: Marc Touissant (SCIoI), "SCIoI Proposal Discussion: Rethinking Decisions and Tasks"
2020-05-07 10:00 - 11:00 | On ZOOM (Contact us for Link)
ABSTRACT:
The goal of this presentation is to discuss a potential project
proposal within RU2 of SCIoI, in particular, to initiate a discussion
with researchers from the analytic side. I will first briefly
introduce our recent work on physical reasoning and manipulation
planning. This work required us to develop elaborate solvers which
influenced my view on the notion of decisions. For instance, “early”
decisions in the reasoning process concern higher abstractions and
future constraints — but mainly because the solver has limited
capacity and relies on decomposition. In that view, decisions are a
means of decomposition. Other interesting aspects concern the
perseverance and switching of (higher) decisions during reasoning and
execution. I am curious to discuss relations to models of decision
making in the analytical sciences and potential future projects.
