Oliver Brock (SCIoI): Genesis, Goals, and Gossip of SCIoI
2020-06-18 16:00 - 17:30 (Europe/Berlin) | On ZOOM (Contact us for Link)
Abstract: I would like to give a personal perspective of the scientific motivation and framing of SCIoI and relate them to the research of my lab, the Robotics and Biology Laboratory. But at the same time, I would like to critically question and discuss all of these things, in an attempt to move towards a shared understanding of what we are trying to accomplish as a cluster. And if we run out of exciting scientific topics (and you are curious about it), I can also talk about the history and soap opera of SCIoI, a story that started more than 10 years ago.
***Want to attend this lecture? Subscribe to our mailing list here or by sending an empty email to scioi-info-join@lists.tu-berlin.de
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

PresFutures Forum, SCIoI’s Fishbowl Discussion: “Predictive AI — Crystal Ball To See the Future or a Threat to Civil Rights?”
2020-06-23 16:00 - 17:00
Rainer Mühlhoff and John-Dylan Haynes participated in a fishbowl discussion on predictive AI.

Thursday Morning Lectures: Dr Utku Culha (Max Planck Inst.): Physical Intelligence on Soft Robots: Order, Functionality, and Adaptation From the Bottom-Up
2020-06-25 10:00 - 11:00 | On ZOOM (Contact communication@scioi.de for link)
Abstract:
We typically have a clear idea about the final design and functionality of a robot before we start building it. We apply this top-down design approach to a wide range of robotic systems and it allows our robots to be more optimized, autonomous, and programmable. However, if we want to design and actuate multiple robots in miniature scales or robots made of soft and deforming materials, this approach sometimes fails to meet our needs. In such cases, we adopt nature’s design strategy that creates complex and emergent morphologies, and adaptive functions out of the collective motion of many neighboring, soft, smaller, and simpler elements. In this talk, I will describe how we can use this bottom-up design approach to build and control soft robots and their self-assemblies in multiple length scales. I will talk about how we can benefit from engineering tools, fundamental laws of physics, and emerging machine learning methods to explore the vast design and function search space of soft robots. I will give examples from my works on embodied intelligence where the physical properties of the robots enable further increments to computational intelligence while multiplying the effects of adaptivity, durability, and autonomy. Our findings can enable novel robotic systems in medicine, agriculture, and human-robot interaction, and establish stronger connections with biology, physics, and material science.
Bio:
Utku Culha has received his bachelor’s and master’s degrees from Bilkent University, Turkey from the Computer Engineering Department. He started his Ph.D. on Mechanical Engineering in ETH-Zurich, Switzerland with Prof. Fumiya Iida and then moved to the University of Cambridge, UK to help establish the Bio-Inspired Robotics Laboratory. During his Ph.D., Utku has worked on deforming thermoplastic materials to build robots with adaptive sensing, locomotion, and manipulation skills. After completing his Ph.D., Utku joined the Physical Intelligence Department at the Max-Planck Institute (MPI) for Intelligent Systems in Stuttgart, Germany, and has been working as a Humboldt Postdoctoral researcher with Prof. Metin Sitti since 2016. Utku is interested in creating self-assembling soft robots that can physically adapt to their environment by deforming their body morphologies. He is also working on using data-efficient machine-learning methods to explore novel robot functions, designs, and controllers.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)
(Image copyright Utku Culha)

Jacqueline Gottlieb (Hosted by Martin Rolfs): Curiosity and Information Demand: How We Can Study Them and Why We Should Care
2020-06-25 16:00 - 18:00 | On ZOOM (Contact us for Link)
Curiosity and information demand: how we can study them and why we should care
A rapidly growing literature has recently emphasized the importance of our sense-making instincts, including complex investigative behaviors such as curiosity, for behavior and brain function. While much of this literature has focused on simple forms of decision making, we explored its significance for attention allocation. To make adaptive decisions in realistic multi-dimensional environments, animals must infer the relevant features and afford them priority for the control of learning and actions. Prioritizing sources of information is the role of executive control and attention, but its neural mechanisms are poorly understood. I will review studies of information demand suggesting that the fronto-parietal network encodes both optimal and non-optimal mechanisms for attentional prioritization. Converging evidence shows that parietal neurons encode prior uncertainty and likelihood, two quantities required for Bayesian prioritization that maximizes the reduction in uncertainty. However, the neurons also encode priority based on hedonic stimulus-reward associations, in ways that seem non-optimal and interfere with the reduction of uncertainty. Continued studies of information demand will shed light on the vital question of how animals make complex decisions in realistic settings – specifically, how they endogenously assign salience or priority to competing sources of information that subsequently control learning and actions.
Jacqueline Gottlieb, Department of Neuroscience, The Kavli Institute for Brain Science, The Zuckerman Institute for Mind Brain and Behavior, Columbia University, New York, NY, 10032, www.gottlieblab.com
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

(Photo by JR Korpa on Unsplash)

PI Lecture: Thorsten Pachur (SCIoI): Ecologically Rational Decision Making
2020-07-02 16:00 - 17:30 | On ZOOM (Contact us for Link)
Ecologically rational decision making
How do we make inferences about a world full of uncertainty and given the mind’s natural bounds in computational abilities? I present a perspective according to which the decision maker is equipped with a repertoire of strategies, containing both simple heuristics and more complex strategies that are adaptive under different ecological and cognitive conditions. I will sketch methodological approaches for studying this “adaptive toolbox” and give an overview of empirical investigations of it. The results suggest that strategy selection in human decision making exploits and is adaptive to both the statistical structure of the environment (e.g., redundancy between cues) and internal factors of the decision maker (e.g., cognitive abilities, knowledge). Further, the use of simple heuristics often seems to occur strategically and efficiently, implementing bounded and ecological rationality.
The Zoom Link will be sent the Monday before the lecture to all our subscribers. (Contact communication@scioi.de for specific questions. We will try to accommodate late link requests where possible)

Thursday Morning Talk: Leon Sixt (Biorobotics Lab, FU Berlin): Opportunities and Challenges in Interpetable ML
2020-07-09 10:00 - 11:00 | On ZOOM (Contact us for Link)
Abstract: Deep neural networks underlie many state of the art solutions to hard problems in computer vision, natural language processing or playing Go. Yet, their power comes with a price. Deep networks transform inputs gradually into outputs, using many parameters and intermediary activations. Understanding what a network has learned, how inputs are mapped to outputs, is inherently difficult. In my talk I will focus on attribution methods, algorithms that provide an explanation as to which input variables were relevant for the network’s decision. I will present some of my recent work in this field by first showing how attribution methods may fail and then presenting a new method that is based on information bottlenecks. In the remainder of my talk I will discuss the challenges we face in interpretable ML and how it may provide the opportunity to gain insight into the datasets themselves.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Work-in-Progress Talk: Dimitri Coelho Mollo (SCIoI) & Alfredo Vernazzani (Ruhr Universität Bochum): Saving Representational Formats: A Computational Theory
2020-07-16 10:00 - 11:00 | On ZOOM (Contact us for Link)
Abstract
Most cognitive sciences (including AI) appeal to representations in explaining (or trying to create) systems capable of cognition, and especially of complex, intelligent behaviour. In philosophy, considerable attention has been dedicated to the problem of explaining in scientifically-acceptable ways how representations come to represent what they do. In contrast, there has been much less effort dedicated to developing theories of representational formats, i.e. those properties of representations traditionally conceived in terms of dichotomies that oppose the symbolic to the iconic, the digital to analogue, and so on. For the most part, work on representational formats has focused on their distinctive phenomenological features; while philosophers have tended largely to remain vague about formats’ explanatory role in cognitive theories and their computational roles in the cognitive system.
In this talk, we propose a new computation-based theory of representational formats that makes room for a plurality of distinguishable formats across a number of different dimensions — such as density, continuity, similarity, etc. — thus avoiding partial or simplistic dichotomies, and neatly individuating the nature and role of representational formats in explaining cognition and intelligent behavior. According to our proposal, representational formats are to be understood primarily in terms of their abstract computational profiles, that is, the coarse-grained computational transformations that they allow. In cashing out this computation-based account of representational formats, we rely on recent advances in understanding the nature of computation in physical systems brought forth by the teleomechanistic view of computation.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

SCIoI Scientific Networking Days (internal event)
2020-08-11 09:00 - 2020-08-13 18:00 | Internal Event
The SCIoI Scientific Networking Days event is an internal retreat meant to establish scientific connections among the people and the projects in SCIoI. Through this event, we want to emphasize the importance of establishing scientific connections among SCIoI researchers and promote in-depth scientific discussions and exchanges.
During the retreat, the SCIoI executive board will evaluate currently pending proposals in the SCIoI internal funding program as well as all ongoing SCIoI projects. The goal is to ensure the scientific quality of the projects and also to guarantee that the projects provide a suitable scientific backdrop for PhDs’ and Postdocs’ careers.
Due to the Covid19-related restrictions, this year all SCIoI members will be asked to hold their talks online. When preparing their presentations, members should keep in mind the varied audience and the cluster’s multi-disciplinary component. In the evening of 11 August, we are also planning a weather-dependent (and entirely optional) social event to be held in Tiergarten park. We will provide more information about this closer to the date. SCIoI Members should also check their calendars for more detailed daily schedules.

Thursday Morning Talk with Rico Jonschkowski (Google Brain): Perception in Motion
2020-09-03 10:00 - 11:00 | On ZOOM (Contact us for Link)
Title: Perception in Motion
Abstract: This is a talk on perception in two parts. Part one exemplifies the “movement” of the field of learning-based robot perception. Here, I will give one example for increasing structural assumptions and one for decreasing them based on our work on differentiable mapping and differentiable resampling. Part two takes the title more literally and investigates the role of motion for learning robotic perception. In that part, I will talk about using motion as a cue for unsupervised learning of optical flow, ego-motion estimation, monocular depth estimation, and object detection.
Bio: Rico Jonschkowski is a research scientist at Robotics at Google, working on unsupervised learning for robot perception. His research vision is to identify structural invariances from the perspective of a learning agent in our world and to inject those invariances as priors into learning algorithms to make robot learning more efficient. Before joining Google in 2018, Rico received his Dr. rer. nat. (German PhD equivalent) from Technische Universität Berlin and his MSc and BSc from Freie Universität Berlin. He was part of the RBO team that won the Amazon Picking Challenge 2015 and received the best systems paper award at Robotics: Science and Systems (RSS) in 2016.

(Photo by Franck V. on Unsplash)

Thursday Morning Talk With Benjamin Wild: Social Networks Through Time – Individuality in a Colony of Honey Bees
2020-09-10 10:00 - 11:00 | On ZOOM (Contact us for Link)
ABSTRACT:
In many social systems, an individual’s role is reflected by its interactions with other members of the group. In many model organisms, and particularly in social insects, the patterns of actions and interactions among individuals are not static but constantly evolving over time. This can be due to the emergence or demise of certain individuals, changing task allocation because of temporal polyethism and changes in the environment, or many other reasons. Understanding such temporal patterns in complex social networks remains a challenging problem. In this talk, I will present two recent approaches we have developed to extract meaningful and inherently interpretable embeddings of the social behavior of honey bees from temporal interaction matrices. The embeddings allow us to describe an individual’s role in the colony at any point during her life, to detect clusters of social development of individuals, to compare the structure of the networks at different times, and to compare the role of individuals in the social structure in a meaningful way even when they were never alive at the same time.

(Photo by Nathaniel Sison on Unsplash)

Guy Theraulaz, (CNRS, Toulouse, France. Host: Pawel Romanczuk): Ethological Analysis and Computational Modeling of Social Interactions in Schooling Fish
2020-10-22 16:00 - 17:30
Abstract: Swarms of insects, schools of fish and flocks of birds display an impressive variety of collective movement patterns that emerge from interactions among group members. These puzzling phenomena raise a variety of questions about the interaction rules that govern the coordination of individuals’ motion and the emergence of large-scale patterns. While numerous models have been proposed, there is still a strong need for detailed experimental studies to foster the biological understanding of such collective motion phenomena. I will first describe the methods that we have developed in the recent years to characterize social interactions between individuals involved in the coordination of swimming in Rummy-nose tetra (Hemigrammus rhodostomus) from data gathered at the individual scale. This species of tropical fish performs burst-and-coast swimming behavior that consists of sudden heading changes combined with brief accelerations followed by quasi-passive, straight decelerations. Our results show that both attraction and alignment behaviors control the reaction of fish to a neighbor. Then I will present how these results can be used to build a model of spontaneous burst-and-coast swimming and social interactions of fish, with all parameters being estimated or directly measured from experiments. This model shows that the simple addition of the pairwise interactions with two neighbors quantitatively reproduces the collective behavior observed in groups of five fish. Increasing the number of interacting neighbors does not significantly improve the simulation results. Remarkably, we find that groups remain cohesive and polarized even when each agent only interacts with only one of its neighbors: the one that has the strongest contribution to the heading variation of the focal agent. Finally, I will present a swarm robotic platform with which we investigate the impact of collision avoidance based on speed control on the group behavior. This platform combines the implementation of the fish behavioral model and an engineering-minded control system to deal with real-world physical constraints. Remarkably, and as already observed in the model simulations, even when robots only interact with their most influential neighbor, our results show that the group remains highly cohesive and polarized while reproducing the behavioral patterns observed in groups of fish in experimental conditions. Overall, our results suggest that fish have to acquire only a minimal amount of information about their environment to coordinate their movements when swimming in groups.

Short bio: Guy Theraulaz is a senior research fellow at the National Center for Scientific Research (CNRS) and an expert in the study of collective animal behaviors. He is also a researcher in the field of swarm intelligence, primarily studying social insects but also distributed algorithms, e.g. for collective robotics, directly inspired by nature. His research focuses on the understanding of a broad spectrum of collective behaviors in animal societies by quantifying and then modeling the individual level behaviors and interactions, thereby elucidating the mechanisms generating the emergent, group-level properties. He has published many papers on nest construction in ant, wasp and termite colonies, collective decision-making in ants and cockroaches, collective motion in fish schools and human crowds and collective estimation in human groups. He has also coauthored five books, among which Swarm Intelligence: From Natural to Artificial Systems (Oxford University Press, 1999) and Self-organization in biological systems (Princeton University Press, 2001) that are now considered as reference textbooks. In 2019, he has been appointed visiting chair professor in Collective Behavior, at the Indian Institute of Science in Bangalore by the Infosys Foundation.

Webpage: http://crca.cbi-toulouse.fr/en/guytheraulaz/

The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Giovanni Pezzulo, ISTC-CNR Rome (Host: Verena Hafner): Human Sensorimotor Communication During Human Joint Action: Experimental and Computational Perspectives
2020-10-29 11:00 - 12:30
Giovanni Pezzulo is a researcher at the Institute of Cognitive Sciences and Technologies, National Research Council in Rome, Italy. His research centers on the neuronal and computational mechanisms of predictive processing, goal-directed behaviour, and the sensorimotor foundations of higher cognition.
Human sensorimotor communication during human joint action: experimental and computational perspectives
During online social interactions, humans engage in various forms of non-linguistic communication. I will discuss recent research in my lab and others about sensorimotor communication (SCM): the study of the subtle communicative signals embedded within our everyday pragmatic actions. SMC is ubiquitous during realistic social interactions. For example, soccer players often carve their body movements in ways that are informative for their teammates or deceptive for their adversaries. Furthermore, we have many ways to perform the same goal-directed action – say, offer a glass of wine – and small kinematic differences can make the same action rude, polite or snobbish, thus potentially unveiling our hidden intentions. I will present some human-human experiments on SMC and discuss them in the context of a theoretical and computational model that we have been developing, and which considers both the costs and benefits of SMC (e.g., in terms of increased interaction success). More broadly, I will discuss our current understanding of the computational (and, in part, neural) mechanisms underlying social interaction at large, including e.g., action observation, prediction and planning mechanisms.
—
Re background material:
For a good introduction https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0079876Photo by Uriel SC on Unsplash
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Berlin Science Week Talk: Alex Kacelnik, Are WE More Like We Think THEY Are, or Are THEY More Like We Think WE Are?
2020-11-04 18:00 - 19:00
As part of the “6 o’clock with SCIoI” talk series within the Berlin Science Week 2020, Prof. Alex Kacelnik will take us on a fascinating journey through the understanding of intelligence in humans, animals and robots.
Please visit the Berlin Science Week website to access the event.
https://falling-walls.com/event/are-we-more-like-we-think-they-are-or-are-they-more-like-we-think-we-are/

Robert Lange (SCIoI): “Learning Not To Learn, Nature Versus Nurture In Silico”
2020-11-05 10:00 - 11:00
Abstract: Animals are equipped with a rich innate repertoire of sensory, behavioral and motor skills, which allows them to interact with the world immediately after birth. At the same time, many behaviors are highly adaptive and can be tailored to specific environments by means of learning and exploration. In this work, we use mathematical analysis and the framework of meta-learning (or ‘learning to learn’) to answer when it is beneficial to learn such an adaptive strategy and when to hard-code a heuristic behavior. We find that the interplay of ecological uncertainty, task complexity and the agents’ lifetime has crucial effects on the meta-learned amortized Bayesian inference performed by an agent. There exist two regimes: One in which meta- learning yields a learning algorithm that implements task-dependent exploration and a second regime in which meta-learning imprints a purely exploitative and ‘hard-coded’ behavior. Further analysis reveals that non-adaptive behaviors are not only optimal for aspects of the environment that are stable across individuals, but also in situations where an adaptation to the environment would in fact be highly beneficial, but could not be done quickly enough to be exploited within the remaining lifetime. Hard-coded behaviors should hence not only be those that always work, but also those that are too complex to be learned within a reasonable time frame.
Link: https://arxiv.org/abs/2010.04466
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Lars Lewejohann (SCIoI): What’s on a Mouse’s Mind? Behavioral Measures To Understand Animal’s Experiences and Needs
2020-11-05 16:00 - 17:30 | On ZOOM (Contact us for Link)
What’s on a mouse’s mind? Behavioral measures to understand animal’s experiences and needs
Lars Lewejohann, Freie Universität Berlin, German Federal Institute for Risk Assessment (BfR), German Centre for the Protection of Laboratory Animals (Bf3R)
Abstract: Mice, as all other living creatures, have adapted to specific living conditions in the course of evolution. From our human point of view, the behavior of animals is therefore not always easy to understand. This applies not only to the question of whether mice are actually capable of behaving intelligently, but also to the question of what is necessary for optimizing animal welfare of laboratory animals. In our work, we are interested in both questions and follow an animal-centered approach asking the mice about “their view”. Of course mice cannot fill out questionnaires, but we have developed a series of behavioral tests that allow to query the animals. In this lecture I will outline our approach with regard to improving housing and living conditions as well as the implications of using mice as a model species for the science of intelligence.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Berlin Science Week Talk: Marc Toussant (SCIoI), How AI Research Makes us Rethink our Intelligence
2020-11-06 18:00 - 19:00
The more we learn about AI, the more we may wonder what this tells us about our own intelligence.
As part of the “6 o’clock with SCIoI” series of talks within the Berlin Science Week, Marc Toussaint will talk about how AI research often raises interesting questions about our own human intelligence.
The more AI research aims to understand notions such as rationality, thinking fast & slow, learning, as well as
creativity and explainability, the more we may wonder what this tells us about ourselves. In what sense do we actually make decisions? Are we optimal or rational? Are we creative? And why should we care to think?
While AI research might not provide the answers, this talk will discuss how concrete findings of AI research make us rethink such questions. The talk is followed by a discussion session with the audience.
Please visit the Berlin Science Week website to access the event.
https://falling-walls.com/event/how-ai-research-makes-us-rethink-our-intelligence/

Berlin Science Week Talk, Pawel Romanczuk And Ralf Kurvers (SCIoI), Collective Intelligence or Collective Stupidity? What Humans can Learn from Fish
2020-11-07 18:00 - 19:00
Exploring swarm intelligence in fish and humans.
As part of the “6 o’clock with SCIoI” talk series, scientists Pawel Romanczuk and Ralf Kurvers will explore swarm intelligence in fish and humans, investigating the role of single individuals and social interactions in collective decisions, also exploring when collectives make good decisions, and when they go wrong.
Please visit the Berlin Science Week website to access the event.
https://falling-walls.com/event/collective-intelligence-or-collective-stupidity-what-humans-can-learn-from-fish/

Berlin Science Week Talk, Michael Pauen (SCIoI): Is artificial intelligence intelligent?
2020-11-09 18:00 - 19:00
A talk about the relation between human and artificial intelligence.
As part of the 6 o’clock with SCIoI series of talks, Michael Pauen will discuss the relation between human and artificial intelligence. The most advanced AI systems today try to drive cars, care for the elderly, read texts or play soccer – things that we do not regard as particularly intelligent at least when they are done by humans. This raises the question whether human and artificial intelligence can be compared at all? Our speaker will suggest a number of criteria that apply to human and artificial intelligence and describe fields where a comparison between humans and robots makes sense. It will turn out that this comparison may teach us something new and unexpected about human intelligence as well.
Please visit the Berlin Science Week website to access the event.
https://falling-walls.com/event/is-artificial-intelligence-intelligent/

Berlin Science Week Panel Discussion: Dimitri Coelho Mollo, Rainer Mühlhoff, Ingo Schulz-Schaeffer, Lynn Schmittwilken. Living with AI: Past, Present, and Future
2020-11-10 18:00 - 19:00
Artificial Intelligence: a philosophical, ethical and social overview.
As part of the series “6 o’clock with SCIoI” series of talks within the Berlin Science Week, the panelists will discuss with the public about the philosophical, ethical and social issues raised by AI research and applications.
Please visit the Berlin Science Week website to access the event.
https://falling-walls.com/event/panel-discussion-living-with-ai-past-present-and-future/

Heiko Hamann, Minimize Surprise in Robots: An Innate Motivation for Collective Behavior
2020-11-12 10:00 - 11:30
Minimize Surprise in Robots: An Innate Motivation for Collective Behavior
After a quick overview of other related research projects in my lab (bio-hybrid systems, swarm performance, collective decision-making), I will present our work on minimize surprise for multi-robot systems. Each robot has two artificial neural networks, a world model (“prediction machine”) and a behavioral module (“action selection network”), that are trained concurrently. There is no predefined task, instead the swarm is rewarded for making correct predictions about future sensory input. As an effect, robots discover behaviors introducing predictable spatiotemporal sensor patterns. I will present simulated results for flocking, aggregation, self-assembly, construction, and first results using real-world mobile robots.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Pawel Romanczuk (SCIoI): Collective Information Processing - From Simple Flocking Models to Real Ecological Systems
2020-11-19 16:00 - 17:30 | On ZOOM (Contact us for Link)
Collective Information Processing – From Simple Flocking Models to Real Ecological Systems
Abstract:
Collective systems such animal groups or cellular ensembles represent fascinating examples of self-organization in biology. In contrast to non-living physical systems, self-organized biological collectives are results of long-term evolutionary adaptations to a specific ecological niche, where collective behavior provides evolutionary benefits to individual agents. However, collective information processing, as an important biological function and a core aspect of collective intelligence, is always subject to constraints set by the interaction mechanisms and the resulting self-organized dynamics.
In this lecture, we will review models of self-organized flocking, discuss their potential limitations, open question, and newer developments. Further on, we will discuss the interplay between self-organization and collective information processing with some specific examples from our recent research, as e.g. collective migration in complex environments, or collective predator evasion.

Michele Rucci, University of Rochester (Hosted by Marianne Maertens): Seeing by Moving: The Indissoluble Bond Between Perception and Action
2020-11-26 16:00 - 18:00
Seeing by moving: the indissoluble bond between perception and action
Establishing a representation of space is a major goal of sensory systems. Spatial information, however, is not always explicit in the incoming sensory signals. In most modalities it needs to be actively extracted from cues embedded in the temporal flow of receptor activation. Vision, on the other hand, starts with a sophisticated optical imaging system that explicitly preserves spatial information on the retina. This may lead to the assumption that vision is predominantly a passive spatial process: all that is needed is to transmit the retinal image to the cortex, like uploading a digital photograph, to establish a spatial map of the world. However, this deceptively simple analogy is inconsistent with theoretical models and experiments that study visual processing in the context of normal motor behavior. I will argue that, as with other senses, vision relies heavily on sensorimotor strategies to extract and represent spatial information in the temporal domain.
Bio:

Michele Rucci investigates the computational and biological mechanisms underlying visual perception following an ecological approach that studies vision in conjunction with motor behavior – in particular eye movements and characteristics of natural environments. In his Active Perception Laboratory, his work has led to multiple findings on the roles of eye movements in the encoding of visual information and the establishment of spatial representations, leading to the development of new tools for experimental studies and robots directly controlled by models of neural pathways.

The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Michael Pauen
2020-12-03 10:00 - 11:00 | On ZOOM (Contact communication@scioi.de for link)
BIO: Michael Pauen is a philosopher with a focus on the philosophy of mind. As the academic director of an interdisciplinary graduate school, he has extensive experience in interdisciplinary research and training. Having a specific interest in philosophical and psychological aspects of human sociality, he will focus on social intelligence both in humans and in artificial systems.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Naomi Leonard, Princeton University (hosted by Jörg Raisch): Opinion Dynamics with Tunable Sensitivity: Consensus, Dissensus, and Cascades
2020-12-03 16:00 - 18:00
I will present a model of continuous-time opinion dynamics for an arbitrary number of agents that communicate over a network and form real-valued opinions about an arbitrary number of options. The model generalizes linear and nonlinear models in the literature. Drawing from biology, physics, and social psychology, we introduce an attention parameter to modulate social influence and a saturation function to bound inter-agent and intra-agent opinion exchanges. This yields simply parameterized dynamics that exhibit the range of opinion formation behaviors predicted by model-independent bifurcation theory but not exhibited by linear models or existing nonlinear models. Behaviors include reliable formation of consensus and dissensus, even in homogeneous networks, and opinion cascades. The opinion dynamics also display ultra-sensitivity to inputs, robustness to disturbance, and flexible transitions between consensus and dissensus. Augmenting the opinion dynamics with feedback dynamics for the attention parameter results in tunable thresholds that govern sensitivity, robustness, and flexibility. The model provides new means for systematic study of dynamics on natural and engineered networks, from information spread and political polarization to collective decision making and dynamic task allocation. This is joint work with Alessio Franci (UNAM, Mexico) and Anastasia Bizyaeva (Princeton).
Naomi Ehrich Leonard is a control theorist whose work involves analysis and design of feedback and interconnection in complex, dynamical systems. She uses mathematical models and methods to study mechanisms of collective motion and collective decision making for multi-agent systems in nature (analysis of animal and human groups) and in engineering (design of autonomous robotic teams and mobile sensor networks). She has applied her work to the collective dynamics of killifish, starlings, honeybees, zebras, and desert harvester ants, as well as to rule-based improvisational dance. She led a multidisciplinary ocean sensing project with a month-long deployment of an automated, adaptive network of underwater robotic vehicles in Monterey Bay, CA. Leonard is the Edwin S. Wilsey Professor of Mechanical and Aerospace Engineering and associated faculty member of the Program in Applied and Computational Mathematics at Princeton University. She is a MacArthur Fellow, a Fellow of the American Academy of Arts and Sciences, IEEE, SIAM, ASME, and IFAC. Visit her website here.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Ralph Hertwig: Experimenting with Intelligence
2020-12-10 16:00 - 17:00 | On ZOOM (Contact us for Link)
Experimenting with Intelligence
Abstract. Within just 7 years, behavioral decision research in psychology underwent a dramatic change. In 1967, Peterson and Beach (1967a) reviewed more than 160 experiments concerned with people’s statistical intuitions. Invoking the metaphor of the mind as an intuitive statistician, they concluded that “probability theory and statistics can be used as the basis for psychological models that integrate and account for human performance in a wide range of inferential tasks” (p. 29). Yet in a 1974 Science article, Tversky and Kahneman rejected this conclusion, arguing that “people rely on a limited number of heuristic principles which reduce the complex tasks of assessing probabilities and predicting values to simple judgmental operations” (p. 1124). With that, they introduced the heuristics-and-biases research program, which has profoundly altered how psychology, and the behavioral sciences more generally, view the mind’s competences, rationality, and, ultimately, intelligence. How was this radical transformation possible? In this talk, I will aim to give one possible answer to this question, and it focuses on the how of we experiment with human intelligence.
Speaker website:
https://www.mpib-berlin.mpg.de/staff/ralph-hertwig
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Patricia Churchland (University of California, San Diego), The Neurobiological Platform for Moral Intuitions
2020-12-17 16:30 - 18:30 | On ZOOM (Contact us for Link)
ABSTRACT: Self-preservation is embodied in our brain’s circuitry: we seek food when hungry, warmth when cold, and mates when lusty. In the evolution of the mammalian brain, circuitry for regulating one’s own survival and well-being was modified. For sociality, the important result was that the ambit of me extends to include others — me-and-mine. Offspring, mates, and kin came to be embraced in the sphere of me-ness; we nurture them, fight off threats to them, keep them warm and safe. The brain knows these others are not me, but if I am attached to them, their plight fires-up caring circuitry, motivating other-care that resembles self-care. In some species, including humans, seeing to the well-being of others may extend, though less intensely, to include friends, business contacts or even strangers, in an ever-widening circle. Oxytocin, an ancient body-and-brain molecule, is at the hub of the intricate neural adaptations sustaining mammalian sociality. Not acting alone, oxytocin works with other hormones and neurotransmitters and structural adaptations. Among its many roles, oxytocin decreases the stress response, making possible the friendly, trusting interactions typical of life in social mammals. I can let my guard down when I know I am among trusted family and friends.

BIO: For decades, Patricia Churchland has contributed to the fields of philosophy of neuroscience, philosophy of the mind and neuroethics. Her research has centered on the interface between neuroscience and philosophy with a current focus on the association of morality and the social brain. A Professor Emeritus of Philosophy at the University of California, San Diego and Adjunct Professor at the Salk Institute, Pat holds degrees from Oxford University, the University of Pittsburg and the University of British Columbia. She has been awarded the MacArthur Prize, The Rossi Prize for Neuroscience and the Prose Prize for Science. She has authored multiple pioneering books, her most recent being Touching a Nerve. She has served as President of the American Philosophical Association and the Society for Philosophy and Psychology. Pat lives in Solana Beach, California, with her husband Paul, a neurophilosopher, and their labradoodle Millie. They have two children, Anne and Mark, both neuroscientists. Read more about her work on her website.
Patricia Churchland is also a member of SCIoI’s Scientific Advisory Board.

Olaf Hellwich
2021-01-07 16:00 - 17:30
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

Thursday Morning Lecture With John A. Nyakatura (MoA), “Reverse-Engineering the Locomotion of a Stem Amniote – Insights From a Multidisciplinary Approach”
2021-01-14 10:00 - 11:00
Reconstructing the locomotion of key vertebrate fossil specimens offers insights into their palaeobiology and helps to conceptualize major transitions in vertebrate evolution. A unique combination of an articulated nearly complete early land-living vertebrate fossil specimen and fossilized trackways was the starting point for an in-depth reconstruction of the locomotion based on the integration of image-based analyses with engineering techniques. The reconstruction involved experimental as well as computer-aided modelling approaches (‘virtual paleontology’). Starting from a large space of potential solutions, unlikely postures and gaits were step-wise excluded based on quantitative data. Research into the fossil’s anatomy, the fossil’s potential joint mobility and simulated potential movements within fossil tracks, a comparative analysis of modern animal locomotor biomechanics using x-ray motion analysis, and finally into a bio-inspired walking machine (OroBOT) will be summarized. The locomotor reconstruction demonstrates that Orobates exhibited more advanced locomotion than has been assumed for earlier species, which suggests that advanced terrestrial locomotion preceded the diversification of crown amniotes, a highly successful group of modern vertebrates. The talk exemplifies how contemporary paleobiological research can be focused on constraint-based exclusion of unlikely scenarios and deals with uncertainty.
The Zoom Link will be sent the day before the lecture. (Contact communication@scioi.de for specific questions)

PI Lecture with Alan Akbik
2021-01-21 16:00 - 17:30

Christa Thöne-Reinecke, “Ethical Justification of Animal Experiments in Germany”
2021-02-04 10:00 - 23:00
All animal ethical positions are largely in agreement that animals – as beings capable of suffering – must be morally considered for their own sake and that certain consequences for one’s own actions must be derived from this.
This insight has been incorporated into animal protection legislation based on the EU Directive 2010/63.
German legislation requires a reasonable justification of the pain, suffering, and harm inflicted on animals.
For this reason, every scientist must demonstrate ethical justifiability of the intended experiment in accordance with the principle of proportionality within the framework of the approval procedure of animal experiments.
More specifically, it must be demonstrated that no alternative method in reaching the project´s aims exists. Furthermore, the project´s indispensability must be scientifically explained and it must be assigned to a permissible purpose. Study planning must be carried out by implementing statistical methods to reduce the number of animals and their burden to the indispensable level.
Animal keeping and medical care must be ensured by the permission to keep and breed animals in the context of a culture of care.
Ultimately, the expected gain in knowledge must be set in relation to the burden inflicted on the animals and must be ethically justifiable or may even be considered an ethical imperative.
The scientist´s proposal and declarations are then revised by the animal welfare officer and, if applicable, by the ethics committee of respective institution.
It is then further examined by the local authorities and the §15 Commission, in which ethics experts and animal welfare organizations are actively involved.
After this revision process, also involving the responsible scientist, the final examination and approval is carried out by the local authorities.
It must be considered that ethical concepts and attitudes of society may be subject to change in the course of time. Hence, a high degree of transparency is necessary in order to maintain public approval.
The Zoom Link will be sent the day before the lecture.
