Contextual learning in the neurosolver

Andrzej Bieszczad, Kasia Bieszczad

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

6 Scopus citations

Abstract

In this paper, we introduce an enhancement to the Neurosolver, a neuromorphic planner and a problem solving system. The enhanced architecture enables contextual learning. The Neurosolver was designed and tested on several problem solving and planning tasks such as re-arranging blocks and controlling a software-simulated artificial rat running in a maze. In these tasks, the Neurosolver learned temporal patterns independent of the context. However in the real world no skill is acquired in vacuum; Contextual cues are a part of every situation, and the brain can incorporate such stimuli as evidenced through experiments with live rats. Rats use cues from the environment to navigate inside mazes. The enhanced architecture of the Neurosolver accommodates similar learning.

Original languageEnglish (US)
Title of host publicationArtificial Neural Networks, ICANN 2006 - 16th International Conference, Proceedings
PublisherSpringer Verlag
Pages474-484
Number of pages11
ISBN (Print)3540386254, 9783540386254
DOIs
StatePublished - 2006
Externally publishedYes
Event16th International Conference on Artificial Neural Networks, ICANN 2006 - Athens, Greece
Duration: Sep 10 2006Sep 14 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4131 LNCS - I

Other

Other16th International Conference on Artificial Neural Networks, ICANN 2006
Country/TerritoryGreece
CityAthens
Period9/10/069/14/06

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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