Karl Tuyls is a Professor of Computer Science at the University of Liverpool, UK and is also a part-time Professor of BioInspired Robotics and Autonomous Systems at Delft University of Technology, the Netherlands. Previously, he held positions at the Vrije Universiteit Brussel, Hasselt University, Eindhoven University of Technology, and Maastricht University. Prof. Tuyls has received several awards and honourable mentions with his research, amongst which: the Information Technology prize 2000 in Belgium, best demo award at AAMAS’12, winner of the German Open robocup@work competitions in 2013 and 2014, world champion of the RoboCup@Work competition in 2013. Furthermore, his research has received substantial attention from national and international press and media (http://tuyls.com). He is on the editorial board of the Journal of Autonomous Agents and Multi-Agent Systems and is editor-in-chief of the Springer briefs series on Intelligent Systems. Prof. Tuyls is also a member of the board of directors of the International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS).
Bio-Inspired Autonomous Systems and Robotics
Bio-inspired autonomous systems investigate principles of sensory motor control, autonomy, evolution and coordination from biological systems for the design of advanced robots. Through abstraction of the design principles of biological systems, techniques can be developed for the control of dynamic robotic systems, decision making, adaptability, and computational optimization. An important challenge in robotics is to create adaptive systems that are able to autonomously operate in diverse environments and are capable of learning from this environment and their peers in order to tackle complex tasks. For this purpose we investigate bio-inspired techniques such as swarm intelligence (social insect behavior as found in honeybees and ants), reinforcement learning, evolutionary algorithms, and evolutionary game theory. In this talk I will sketch some of the major challenges in this research area and will overview some ongoing research projects that use bio-inspired techniques for coordination, learning and control in robotic systems.