On the Capabilities of Pointer Networks for Deep Deductive Reasoning

06/17/2021
by   Monireh Ebrahimi, et al.
17

The importance of building neural networks that can learn to reason has been well recognized in the neuro-symbolic community. In this paper, we apply neural pointer networks for conducting reasoning over symbolic knowledge bases. In doing so, we explore the benefits and limitations of encoder-decoder architectures in general and pointer networks in particular for developing accurate, generalizable and robust neuro-symbolic reasoners. Based on our experimental results, pointer networks performs remarkably well across multiple reasoning tasks while outperforming the previously reported state of the art by a significant margin. We observe that the Pointer Networks preserve their performance even when challenged with knowledge graphs of the domain/vocabulary it has never encountered before. To the best of our knowledge, this is the first study on neuro-symbolic reasoning using Pointer Networks. We hope our impressive results on these reasoning problems will encourage broader exploration of pointer networks' capabilities for reasoning over more complex logics and for other neuro-symbolic problems.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

10/12/2020

Neural-Symbolic Reasoning on Knowledge Graphs

Knowledge graph reasoning is the fundamental component to support machin...
08/24/2018

Ontology Reasoning with Deep Neural Networks

The ability to conduct logical reasoning is a fundamental aspect of inte...
06/06/2017

Unsupervised Neural-Symbolic Integration

Symbolic has been long considered as a language of human intelligence wh...
11/27/2021

Common Sense Knowledge Learning for Open Vocabulary Neural Reasoning: A First View into Chronic Disease Literature

In this paper, we address reasoning tasks from open vocabulary Knowledge...
12/15/2020

Object-based attention for spatio-temporal reasoning: Outperforming neuro-symbolic models with flexible distributed architectures

Neural networks have achieved success in a wide array of perceptual task...
05/06/2021

A Generative Symbolic Model for More General Natural Language Understanding and Reasoning

We present a new fully-symbolic Bayesian model of semantic parsing and r...
06/03/2019

Deep Reasoning Networks: Thinking Fast and Slow

We introduce Deep Reasoning Networks (DRNets), an end-to-end framework t...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.