Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills
Julia Tan,Ransalu Senanayake,Fabio Ramos,Julia Tan,Ransalu Senanayake,Fabio Ramos
Deep reinforcement learning (RL) is a promising approach to solving complex robotics problems. However, the process of learning through trial-and-error interactions is often highly time-consuming, despite recent advancements in RL algorithms. Additionally, the success of RL is critically dependent on how well the reward-shaping function suits the task, which is also time-consuming to design. As ag...
