4 papers
DiAReL: Reinforcement Learning with Disturbance Awareness for Robust Sim2Real Policy Transfer in Robot Control
Mohammadhossein Malmir, Josip Josifovski, Noah Klarmann +1
Delayed Markov decision processes (DMDPs) fulfill the Markov property by augmenting the state space of agents with a finite time window of recently committed actions. In reliance o…
Safe Continual Domain Adaptation after Sim2Real Transfer of Reinforcement Learning Policies in Robotics
Josip Josifovski, Shangding Gu, Mohammadhossein Malmir +5
Domain randomization has emerged as a fundamental technique in reinforcement learning (RL) to facilitate the transfer of policies from simulation to real-world robotic applications…
Continual Domain Randomization
Josip Josifovski, Sayantan Auddy, Mohammadhossein Malmir +3
Domain Randomization (DR) is commonly used for sim2real transfer of reinforcement learning (RL) policies in robotics. Most DR approaches require a simulator with a fixed set of tun…
State Representations as Incentives for Reinforcement Learning Agents: A Sim2Real Analysis on Robotic Grasping
Panagiotis Petropoulakis, Ludwig Gräf, Mohammadhossein Malmir +2
Choosing an appropriate representation of the environment for the underlying decision-making process of the reinforcement learning agent is not always straightforward. The state re…