At the institute for neural information processing we are interested in the information processing principles underlying biological systems that perceive, learn and act and to exploit these principles for technical systems. Compared to their technical counterparts, biological systems are often extremely robust and adaptive, even though they are made up of components that seem much less reliable than typical components in technical devices. To understand these different information processing strategies requires a highly interdisciplinary approach at the crossroads of computer science, engineering, psychology and biology. Our research methods include theoretical analyses and computer simulations in the design of artificial learning systems including experiments with neuromorphic hardware and robots, but also neural and behavioral data analysis of natural learning systems including behavioral experiments with human subjects in virtual reality environments. The aim of this research is to better understand both biological and artificial intelligence, and where possible to exploit biological information processing principles to improve technical applications.