Logic and the 2-Simplicial Transformer

James Clift, Dmitry Doryn, Daniel Murfet, James Wallbridge

Abstract: We introduce the 2-simplicial Transformer, an extension of the Transformer which includes a form of higher-dimensional attention generalising the dot-product attention, and uses this attention to update entity representations with tensor products of value vectors. We show that this architecture is a useful inductive bias for logical reasoning in the context of deep reinforcement learning.

Code: https://github.com/dmurfet/2simplicialtransformer

Keywords: transformer, logic, reinforcement learning, reasoning

TL;DR: We introduce the 2-simplicial Transformer and show that this architecture is a useful inductive bias for logical reasoning in the context of deep reinforcement learning.