Extending the Associative Rule Chaining Architecture for Multiple Arity Rules

Nathan John Burles; Jim Austin; Simon O'Keefe

Extending the Associative Rule Chaining Architecture for Multiple Arity Rules

Nathan John Burles, Jim Austin, Simon O'Keefe

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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.

Original language	English
Title of host publication	Proceedings of the Ninth International Workshop on Neural-Symbolic Learning and Reasoning
Pages	47-51
Number of pages	5
Publication status	Published - 2013
Event	Ninth International Workshop on Neural-Symbolic Learning and Reasoning - Beijing, China Duration: 5 Aug 2013 → 5 Aug 2013

Conference

Conference	Ninth International Workshop on Neural-Symbolic Learning and Reasoning
Country/Territory	China
City	Beijing
Period	5/08/13 → 5/08/13

Access to Document

extendingARCAForMultipleArityRulesAccepted author manuscript, 173 KB

http://www.neural-symbolic.org/NeSy13/nesy13proceedings.pdf

Cite this

@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",

note = "Ninth International Workshop on Neural-Symbolic Learning and Reasoning ; Conference date: 05-08-2013 Through 05-08-2013",

}

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. <http://www.neural-symbolic.org/NeSy13/nesy13proceedings.pdf>

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

T2 - Ninth International Workshop on Neural-Symbolic Learning and Reasoning

Y2 - 5 August 2013 through 5 August 2013

ER -