5 accepted papers
Reinforcement learning (RL) approaches based on Markov Decision Processes (MDPs) are predominantly applied in the robot joint space, often relying on limited task-specific information and partial awareness of the 3D environment. In contrast, episodic RL has demonstrated advantages over traditional M…
Therapist-in-the-loop robotic rehabilitation has shown the promise to enhance rehabilitation outcomes by integrating the strengths of therapists and robotic systems. However, its broader adoption is limited due to insufficient interaction and limited adaptation capability. This article proposes a no…
Recent advancements in question generation (QG) have been significantly propelled by reinforcement learning (RL). Although extensive reward models have been designed to capture the attributes of ideal questions, their associated learning challenges, particularly in sample efficiency and diversity, r…
The significance of network structures in promoting group cooperation within social dilemmas has been widely recognized. Prior studies attribute this facilitation to the assortment of strategies driven by spatial interactions. Although reinforcement learning has been employed to investigate the impa…
Integrated Task and Motion Planning (TAMP) offers opportunities for achieving generalized autonomy in robots but also poses challenges. It involves searching in both symbolic task space and high-dimensional motion space, while also addressing geometrically infeasible actions within its hierarchical…