A diagram of our model-based reinforcement learning approach is shown in Fig. 2. We maintain a dataset of trajectories that we iteratively add to, and we use this dataset to train our dynamics model.

This student thesis project aims to implement a model-based deep reinforcement learning algorithm for controlling the flow past a cylinder. Therefore, the drlfoam repository, which already provides a ...

Abstract: This paper presents a novel Flow-based reinforcement learning strategy to model agent systems that can adapt to complex and dynamic problem environments by incrementally mastering their ...

This code repository accompanies the article Model-based deep reinforcement learning for accelerated learning from flow simulations. For referencing, please use: @misc{weiner2024, title={Model-based ...

Model-Based Reinforcement Learning (MBRL) algorithms have been shown to have an ... update the distribution and repeat. FIGURE 4. Block diagram of our Eidos environment. Two randomly initialized deep ...

Firstly, this paper studies the corresponding relationship between reinforcement learning method and power system dispatching decision problem, and constructs the artificial intelligent dispatching ...