A policy gradient algorithm integrating long and short-term rewards for soft continuum arm control
The soft continuum arm has extensive application in industrial production and human life
due to its superior safety and flexibility. Reinforcement learning is a powerful technique for …
due to its superior safety and flexibility. Reinforcement learning is a powerful technique for …
Mingling foresight with imagination: Model-based cooperative multi-agent reinforcement learning
Recently, model-based agents have achieved better performance than model-free ones
using the same computational budget and training time in single-agent environments …
using the same computational budget and training time in single-agent environments …
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
Model-based reinforcement learning is one approach to increase sample efficiency.
However, the accuracy of the dynamics model and the resulting compounding error over …
However, the accuracy of the dynamics model and the resulting compounding error over …
Diminishing Return of Value Expansion Methods
Model-based reinforcement learning aims to increase sample efficiency, but the accuracy of
dynamics models and the resulting compounding errors are often seen as key limitations …
dynamics models and the resulting compounding errors are often seen as key limitations …
Revisiting Model-based Value Expansion
Model-based value expansion methods promise to improve the quality of value function
targets and, thereby, the effectiveness of value function learning. However, to date, these …
targets and, thereby, the effectiveness of value function learning. However, to date, these …