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!
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
We constantly move our eyes, approximately three times per second, and even more if we search for something. We do this to place individual objects into the region where we see with highest resolution, the fovea. But can you still find a target if you can not see with your fovea? Or what about if
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
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
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
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
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
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
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
The first conference and exhibition of the Cluster of Excellence Science of Intelligence (SCIoI) in Berlinwas held in September 2023. Leading experts from science and politics, as well as journalists and the broader public came together to discuss the diverse facets of intelligence research. From individual, social, and collective principles of intelligence to the ethics
Abstract: Collective motion is a familiar sight in nature; groups of distinct, self-propelled individuals appear to move as a coherent whole, exhibiting a rich behavioral repertoire that ranges from directed movement to milling to disordered swarming. Biological collective motion is an emergent phenomenon that is the result of self-organization, whereby macroscopic patterns arise from decentralized,
Marchstr. 23 – MAR 5-2
10587 Berlin
Email: info@scioi.de
Tel: +49 30 314 77344
