Emre Uğur

Refining discovered symbols with multi-step interaction experience

2015

In our previous work, we showed how symbolic planning operators can be formed in the continuous perceptual space of a manipulator robot that explored the world with its single-step actions. In this paper, we extend …

Diffusion Policies for Out-of-Distribution Generalization in Offline Reinforcement Learning

2024 · IEEE Robotics and Automation Letters

Offline Reinforcement Learning (RL) methods leverage previous experiences to learn better policies than the behavior policy used for data collection. However, they face challenges handling distribution shifts due to the lack of online interaction during …

Conditional Neural Expert Processes for Learning Movement Primitives from Demonstration

2024 · arXiv (Cornell University)

Learning from Demonstration (LfD) is a widely used technique for skill acquisition in robotics. However, demonstrations of the same skill may exhibit significant variances, or learning systems may attempt to acquire different means of the …