6 papers
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…
Exploration with Intrinsic Motivation using Object-Action-Outcome Latent Space
Melisa Sener, Yukie Nagai, Erhan Oztop +1
One effective approach for equipping artificial agents with sensorimotor skills is to use self-exploration. To do this efficiently is critical, as time and data collection are cost…
Trick the Body Trick the Mind: Avatar representation affects the perception of available action possibilities in Virtual Reality
Tugce Akkoc, Emre Ugur, Inci Ayhan
In immersive Virtual Reality (VR), your brain can trick you into believing that your virtual hands are your real hands. Manipulating the representation of the body, namely the avat…
Time Perception: A Review on Psychological, Computational and Robotic Models
Hamit Basgol, Inci Ayhan, Emre Ugur
Animals exploit time to survive in the world. Temporal information is required for higher-level cognitive abilities such as planning, decision making, communication, and effective…
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…
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…