My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control

Understand

Multitask Reinforcement Learning is a promising way to obtain models with better performance, generalisation, data efficiency, and robustness.

• Most existing work is limited to compatible settings, where the state and action space dimensions are the same across tasks.
• Graph Neural Networks (GNN) are one way to address incompatible environments, because they can process graphs of arbitrary size.
• They also allow practitioners to inject biases encoded in the structure of the input graph.