3 papers
cs.RO2020
Reward Conditioned Neural Movement Primitives for Population Based Variational Policy Optimization
M. Tuluhan Akbulut, Utku Bozdogan, Ahmet Tekden +1
The aim of this paper is to study the reward based policy exploration problem in a supervised learning approach and enable robots to form complex movement trajectories in challengi…
cs.RO2020
ACNMP: Skill Transfer and Task Extrapolation through Learning from Demonstration and Reinforcement Learning via Representation Sharing
M. Tuluhan Akbulut, Erhan Oztop, M. Yunus Seker +3
To equip robots with dexterous skills, an effective approach is to first transfer the desired skill via Learning from Demonstration (LfD), then let the robot improve it by self-exp…
cs.RO2019
Belief Regulated Dual Propagation Nets for Learning Action Effects on Groups of Articulated Objects
Ahmet E. Tekden, Aykut Erdem, Erkut Erdem +3
In recent years, graph neural networks have been successfully applied for learning the dynamics of complex and partially observable physical systems. However, their use in the robo…