Logic and the 2-Simplicial Transformer

James Clift, Dmitry Doryn, Daniel Murfet, James Wallbridge

Keywords: attention, inductive bias, logic, logical reasoning, reasoning, reinforcement learning, transformer

Mon Session 1 (05:00-07:00 GMT) [Live QA] [Cal]
Mon Session 5 (20:00-22:00 GMT) [Live QA] [Cal]

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.

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