 |
| Emre Ugur |
| organizer • speaker |
Bio
Emre Ugur is an Associate Professor in Dept. of Computer Engineering, Bogazici University, the chair of the Cognitive Science MA Program, the vice-chair of the Dept. of Computer Engineering, and the head of the Cognition, Learning and Robotics (CoLoRs) lab.
He received his PhD degree in Computer Engineering from Middle East Technical University (METU, Turkey). He was a research assistant in KOVAN Lab. METU (2003-2009); worked as a research scientist at ATR, Japan (2009-2013); visited Osaka University as a specially appointed Assist.&Assoc. Professor (2015&2016); and worked as a senior researcher in University of Innsbruck (2013-2016). He participated in several projects funded by EU, TUBITAK, and JST. He is currently Principle Investigator of IMAGINE project supported by European Commission, Horizon 2020 Programme; EXO-AI-FLEX project supported by TUBITAK, 1003 program; and DeepSym project supported by TUBITAK, 1001 program.
He is interested in robotics, robot learning, cognitive robotics.
Google scholar page • Personal webpage
Talk
Symbolic planning and reasoning are powerful tools for robots tackling complex tasks. However, the need to manually design the symbols restrict their applicability, especially for robots that are expected to act in open-ended environments. In this talk, I will present our methods that are used to discover action-grounded, object-and-effect symbols and symbolic operators, and build probabilistic rules over them for non-trivial action planning in robotic manipulation tasks.