Thursday Morning Talk

Ulrike Scherer and Sean Ehlman (Science of Intelligence)

MAR 2.057

Abstract: Collective dynamics play a crucial role in everyday decision-making. Whether social influence promotes the spread of accurate information and ultimately results in collective intelligence or leads to false information cascades and maladaptive social contagion depends on the cognitive mechanisms underlying social interactions. This talk will take place in person at SCIoI.    

For the Public

Lange Nacht der Wissenschaften 2023 – Meet Pepper

Who is Pepper? The humanoid robot we use in our labs helps us understand social interactions between robots and humans, and if it’s easy to see why that works so well. Pepper is designed to quickly develop a connection with its human interlocutor. Come and try it for yourself!

For the Public

Lange Nacht der Wissenschaften 2023 – Mohsen Raoufi, “Meet the Swarm Robots”

Swarms, such as schools of fish, and flocks of birds, have shown a great capability of solving complex problems in nature. Such examples are bees finding the best nest site, or fish escaping from a predator. In this demostration Mohsen Raoufi, at the Swarm Robotics Lab of SCIoI, will demonstrate how a swarm of robots

For the Public

Lange Nacht der Wissenschaften 2023 – Exzellentes Pub Quiz

Together with the other six Berlin Clusters of Excellence, we are organizing a quiz night: the Excellent Pub Quiz! This event is expected to attract team players, puzzle enthusiasts, and science fans alike, offering an excellent opportunity to enjoy a summer evening in a relaxed atmosphere while putting your knowledge to the test. The Quiz

Thursday Morning Talk

Mohsen Raoufi (Science of Intelligence), From State Estimation to Collective Estimation, and from Individuality to Complexity in Swarm Robotic Systems

Using swarm optimization algorithms as heuristic solutions in various engineering problems, including the state estimation of nonlinear systems, has been an inspiration to me for my SCIoI project. We started our project by studying the "Wisdom of Crowds" effect, i.e. the notion that the average of many imperfect estimations, under the right conditions, can potentially yield a

PI Lecture

Jörg Raisch (Science of Intelligence), “Efficient Consensus over Wireless Channels & and its Use in Traffic Automation Problems”

MAR 2.057

Consensus algorithms are routinely employed in a variety of multi-agent scenarios. They require that each agent iteratively evaluates a multivariate function of its neighbours’ information states. If a wireless communication channel is used, this is typically implemented through protocols (such as TDMA – Time Division Multiple Access) that avoid superposition of transmitted signals by assigning each transmitter its own

Thursday Morning Talk

Michael Taborsky, “The Evolution of Social Behaviour”

Abstract: The social structure and behaviour of organisms is highly divergent. How can this stunning diversity in nature be explained? I will argue that a few key principles are responsible for the evolution of social behaviour, with all its simple and complex manifestations. Organisms compete for resources. As survival and reproduction require resources and only

Thursday Morning Talk

Santiago Paternain, “Safe Learning for Dynamical Systems and Control”

Abstract: Reinforcement learning has shown great success in controlling complex dynamical systems. However, when training a policy, most algorithms only consider a single objective function. While this may suffice in virtual domains, physical systems must satisfy a set of operational constraints, with safety being of crucial importance. It is natural to express these problems as

Thursday Morning Talk

Lisa-Kristin Richter, “Model Training for Facial Recognition of Raccoons”

MAR 2.057

Machine learning tools have already been used to identify individual animals such as but not limited to pandas, black bears, cows and dogs. These tools can help to improve the quality of non-invasive wildlife monitoring and enhance the information on individual animal behaviour as well as on behaviour within social networks of the animals (Lynn

PI Lecture

Olaf Hellwich (Science of Intelligence), “State Vectors of Computer Vision at Time t=now. Perspectives, Particles and Predictions”

MAR 2.057

We take varying perspectives to the state of the art in Computer Vision: e.g. from SCIoI, disciplinary and interdisciplinary viewpoints. Sampling from the multi-modal state vector distribution, we inspect currently exciting developments: e.g. the integration of computer vision and language processing, the use of biological principles in synthetic systems, and self supervision. Generalizing from the