Decision Making under Uncertainty

Speaker: Joni Pajarinen

Robotics Seminar Series. Next Session – 4th December 2020, 15:00-16:00, via zoom. Link to event:


Our future vision is a world where autonomous robots can enter an unknown unstructured environment, clean up toys, arrange objects in the kitchen, segregate waste, or pick up and lift tree trunks onto a truck. To accomplish this, in a partially unknown environment a rational robot needs to plan its actions so that the robot learns about the environment while performing its assigned tasks. The goal of the research group is to help robots understand what they need to learn in order to perform their assigned tasks, and, thus, make robots capable of operating on their own and pro-actively help humans.

To make autonomous robots a reality the research group focuses on developing machine learning methods and applying them on robots. In this talk we discuss some of our recent advances in manipulation planning under uncertainty, Monte Carlo tree search, policy search and curriculum learning in deep reinforcement learning.