An architecture for pattern recognition and decision-making

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We present a simple brain architecture that allows agents to recognise patterns and make decisions based on those patterns. It takes into account not only the type of situation the agent thinks it is facing, but also how confident the agent is in its assessment, and possible alternatives. An agent using this brain was applied to two classification tasks: Handwritten numeral recognition and spoken numeral recognition. In both cases, its accuracy was comparable to more traditional classifiers. This suggests that the new architecture could be useful as a generalpurpose brain, for agents in a variety of domains.

Original languageEnglish
Title of host publicationFrom Animals to Animats - 14th International Conference on Simulation of Adaptive Behavior, SAB 2016, Proceedings
EditorsJohn Hallam, Elio Tuci, Alexandros Giagkos, Myra Wilson
PublisherSpringer-Verlag GmbH and Co. KG
Pages22-33
Number of pages12
ISBN (Print)9783319434872
DOIs
Publication statusPublished - 2016
Event14th International Conference on Simulation of Adaptive Behavior, SAB 2016 - Aberystwyth, United Kingdom
Duration: 23 Aug 201626 Aug 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9825 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Simulation of Adaptive Behavior, SAB 2016
Country/TerritoryUnited Kingdom
CityAberystwyth
Period23/08/1626/08/16

Keywords

  • Artificial life
  • Automatic speech recognition
  • Decision-making
  • Handwriting recognition

Fingerprint

Dive into the research topics of 'An architecture for pattern recognition and decision-making'. Together they form a unique fingerprint.

Cite this