1 citations · 2 across the 6 of their papers we have counts for
6 papers
Repetition as Reinforcement: Enhancing Sample Efficiency via Instant Episode Repetition in Reinforcement Learning
Hoda Yamani, Yuning Xing, Koen van Rijnsoever +2
Repetition is a fundamental mechanism in human learning, where revisiting successful experiences strengthens memory, consolidates skills, and improves future performance. Motivated…
Bounded Exploration with World Model Uncertainty in Soft Actor-Critic Reinforcement Learning Algorithm
Ting Qiao, Henry Williams, David Valencia +1
One of the bottlenecks preventing Deep Reinforcement Learning algorithms (DRL) from real-world applications is how to explore the environment and collect informative transitions ef…
Benchmarking Reinforcement Learning Methods for Dexterous Robotic Manipulation with a Three-Fingered Gripper
Elizabeth Cutler, Yuning Xing, Tony Cui +8
Reinforcement Learning (RL) training is predominantly conducted in cost-effective and controlled simulation environments. However, the transfer of these trained models to real-worl…
Image-Based Deep Reinforcement Learning with Intrinsically Motivated Stimuli: On the Execution of Complex Robotic Tasks
David Valencia, Henry Williams, Yuning Xing +3
Reinforcement Learning (RL) has been widely used to solve tasks where the environment consistently provides a dense reward value. However, in real-world scenarios, rewards can ofte…
CTD4 -- A Deep Continuous Distributional Actor-Critic Agent with a Kalman Fusion of Multiple Critics
David Valencia, Henry Williams, Yuning Xing +3
Categorical Distributional Reinforcement Learning (CDRL) has demonstrated superior sample efficiency in learning complex tasks compared to conventional Reinforcement Learning (RL)…
Deep Reinforcement Learning for Local Path Following of an Autonomous Formula SAE Vehicle
Harvey Merton, Thomas Delamore, Karl Stol +1
With the continued introduction of driverless events to Formula:Society of Automotive Engineers (F:SAE) competitions around the world, teams are investigating all aspects of the au…