By the same authors

Extending the Associative Rule Chaining Architecture for Multiple Arity Rules

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Standard

Extending the Associative Rule Chaining Architecture for Multiple Arity Rules. / Burles, Nathan John; Austin, Jim; O'Keefe, Simon.

Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning. 2013. p. 47-51.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Burles, NJ, Austin, J & O'Keefe, S 2013, Extending the Associative Rule Chaining Architecture for Multiple Arity Rules. in Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning. pp. 47-51, Ninth International Workshop on Neural-Symbolic Learning and Reasoning, Beijing, China, 5/08/13.

APA

Burles, N. J., Austin, J., & O'Keefe, S. (2013). Extending the Associative Rule Chaining Architecture for Multiple Arity Rules. In Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning (pp. 47-51)

Vancouver

Burles NJ, Austin J, O'Keefe S. Extending the Associative Rule Chaining Architecture for Multiple Arity Rules. In Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning. 2013. p. 47-51

Author

Burles, Nathan John ; Austin, Jim ; O'Keefe, Simon. / Extending the Associative Rule Chaining Architecture for Multiple Arity Rules. Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning. 2013. pp. 47-51

Bibtex - Download

@inproceedings{9cb91ab664954411b3347d91f158d723,
title = "Extending the Associative Rule Chaining Architecture for Multiple Arity Rules",
abstract = "The Associative Rule Chaining Architecture uses distributed associative memories and superimposed distributed representations in order to perform rule chaining efficiently [Austin et al., 2012]. Previous work has focused on rules with only a single antecedent, in this work we extend the architecture to work with multiple-arity rules and show that it continues to operate effectively.",
author = "Burles, {Nathan John} and Jim Austin and Simon O'Keefe",
year = "2013",
language = "English",
pages = "47--51",
booktitle = "Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Extending the Associative Rule Chaining Architecture for Multiple Arity Rules

AU - Burles, Nathan John

AU - Austin, Jim

AU - O'Keefe, Simon

PY - 2013

Y1 - 2013

N2 - The Associative Rule Chaining Architecture uses distributed associative memories and superimposed distributed representations in order to perform rule chaining efficiently [Austin et al., 2012]. Previous work has focused on rules with only a single antecedent, in this work we extend the architecture to work with multiple-arity rules and show that it continues to operate effectively.

AB - The Associative Rule Chaining Architecture uses distributed associative memories and superimposed distributed representations in order to perform rule chaining efficiently [Austin et al., 2012]. Previous work has focused on rules with only a single antecedent, in this work we extend the architecture to work with multiple-arity rules and show that it continues to operate effectively.

M3 - Conference contribution

SP - 47

EP - 51

BT - Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning

ER -