A Best-first Backward-chaining Search Strategy based on Learned Predicate Representations

Alexander Sakharov

Research.Publish.Connect.

*Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

*Please fill out at least one Field.

Name:
Country:
Subject:

Advanced Search Affiliations Search

If you're looking for an exact phrase use quotation marks on text fields.

Proceedings

Proceedings Search *Please fill out at least one Field. *Value must be an number!

Title:
ISBN:
Year:
Acronym:
Subject:

Advanced Search Proceedings Search

If you're looking for an exact phrase use quotation marks on text fields.

Papers

Papers Search *Please fill out at least one Field.

Title:
Author:
Affiliation:
Subject:

Advanced Search Papers Search

If you're looking for an exact phrase use quotation marks on text fields.

Authors

Authors Search *Please fill out at least one Field.

Name:
Affiliation:
Country:
Conference:
Subject:

Advanced Search Authors Search

If you're looking for an exact phrase use quotation marks on text fields.

Advanced Search

Paper

A Best-first Backward-chaining Search Strategy based on Learned Predicate Representations

Topics: Hybrid Intelligent Systems; Knowledge Representation and Reasoning; Knowledge-Based Systems; Neural Networks

In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, 982-989, 2021

Author: Alexander Sakharov

Affiliation: Synstretch, Framingham, MA, U.S.A.

Keyword(s): Knowledge Base, First-order Logic, Resolution, Backward Chaining, Neural-symbolic Computing, Tensorization.

Abstract: Inference methods for first-order logic are widely used in knowledge base engines. These methods are powerful but slow in general. Neural networks make it possible to rapidly approximate the truth values of ground atoms. A hybrid neural-symbolic inference method is proposed in this paper. It is a best-first search strategy for backward chaining. The strategy is based on neural approximations of the truth values of literals. This method is precise and the results are explainable. It speeds up inference by reducing backtracking.

CC BY-NC-ND 4.0

Guest: Register as new SciTePress user now for free.

SciTePress user: please login.

My Papers

You are not signed in, therefore limits apply to your IP address 3.141.8.247

In the current month:

Recent papers: 100 available of 100 total

2⁺ years older papers: 200 available of 200 total

Paper citation in several formats:

Sakharov, A. (2021). A Best-first Backward-chaining Search Strategy based on Learned Predicate Representations. In Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-758-484-8; ISSN 2184-433X, SciTePress, pages 982-989. DOI: 10.5220/0010299209820989

@conference{icaart21,
author={Alexander Sakharov.},
title={A Best-first Backward-chaining Search Strategy based on Learned Predicate Representations},
booktitle={Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2021},
pages={982-989},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010299209820989},
isbn={978-989-758-484-8},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - A Best-first Backward-chaining Search Strategy based on Learned Predicate Representations
SN - 978-989-758-484-8
IS - 2184-433X
AU - Sakharov, A.
PY - 2021
SP - 982
EP - 989
DO - 10.5220/0010299209820989
PB - SciTePress