Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing. (arXiv:2103.01009v3 [cs.LG] UPDATED)

Recent research has shown that graph neural networks (GNNs) can learn
policies for locomotion control that are as effective as a typical multi-layer
perceptron (MLP), with superior transfer and multi-task performance (Wang et
al., 2018; Huang et al., 2020). Results have so far been limited to training on
small agents, with the performance of GNNs deteriorating rapidly as the number
of sensors and actuators grows. A key motivation for the use of GNNs in the
supervised learning setting is their …

arxiv gnns scaling snowflake