Our VRN is an RL-trained neural network architecture that learns to locally refine an initial (value-based) plan in a simplified (2D) problem abstraction.

To this end, our work presents a novel neural network, the. Value Refinement Network (VRN), which implements this promising strategy. Similar to other works ...

Sparse rewards and long decision horizons make agent navigation tasks difficult to solve via reinforcement learning (RL) such as (deep) Q-learning.

Nov 26, 2021 · The Value Refinement Network (VRN) is an architecture that refines a simple plan locally with respect to the full agent state.

Sep 29, 2021 · Combining the benefits of planning and learning values, we propose the Value Refinement Network (VRN), an architecture that locally refines ...

Combining these strengths of RL and planning, we propose the Value Refinement Network (VRN), in this work. Our VRN is an RL-trained neural network architecture ...

The VRN is an RL-trained neural network architecture that learns to locally refine an initial (value-based) plan in a simplified problem abstraction based ...

This article describes the use of the Deep Deterministic Policy Gradient network, a deep reinforcement learning algorithm, for mobile robot navigation. The ...

Combining these strengths of RL and planning, we propose the Value Refinement Network (VRN), in this work. Our VRN is an RL-trained neural network architecture ...

Value refinement network (VRN). J Wöhlke, F Schmitt, H van Hoof. 2, 2022. Learning Hierarchical Planning-Based Policies from Offline Data. J Wöhlke, F Schmitt, ...