SCIoI presents RoboFish at BUA‘s “Crossing Boundaries” conference
The Berlin University Alliance (BUA) event “Crossing Boundaries” took place on 22 November 2023 in the Kulturbrauerei Berlin. The event, attended by over 300 guests, was a platform for diverse perspectives from various disciplines and sectors of society, emphasizing Berlin’s current status as a prime location for science and collaboration across fields like science, politics, economy, culture, and civil society. Science of Intelligence (SCIoI) presented the RoboFish at the event and engaged with the audience about the latest findings of the cluster.
Key speakers at the event included Alexandra-Gwyn Paetz, the Managing Director of the (BUA), who introduced the vision of “Knowledge Lab 2033” and its implications for Berlin’s research and communication space. Prominent topics discussed were the significant transformations occurring in Berlin, as emphasized by Prof. Dr. Johannes Vogel, and the challenges and potential in fostering a welcoming culture for international students and researchers, as addressed by Dr. Michael Harms. Other speakers, like Prof. Dr. Sonja Schimmler and Prof. Dr. h.c. Jutta Allmendinger, PhD, focused on the promotion of Open Science and the development of an integrated research space in Berlin, respectively, catering to researchers at all career stages and fostering interdisciplinary collaboration.
A highlight of the event were the thematic spaces of the Berlin Clusters of Excellence. The seven Clusters showcased their individual contributions form their varied fields of research. SCIoI researchers Jens Krause and David Bierbach presented the RoboFish and the underlying research to the audience. Inspired by the rules that shape fish and bird swarms, the project of this demonstrator explores the complexities of social interactions. Robotic fish take the stage as social partners, replacing living fish in this setup. With adaptive real-time behavior, these “socially competent” robots lead and interact with their counterparts, showcasing their problem-solving skills. The Reinforcement Learning environment trains robots to engage with our artificial fish models, unveiling strategies to tackle tasks effectively. The RoboFish holds immense research potential, fostering collaborations with biologists and roboticists.
