Contextual Learning in the Neurosolver

  • Andrzej Bieszczad
  • Kasia Bieszczad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4131)


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.


Target Node Contextual Learn Place Cell General Problem Solver Context Cell 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Andrzej Bieszczad
    • 1
  • Kasia Bieszczad
    • 2
  1. 1.Computer ScienceCalifornia State University Channel IslandsCamarilloUSA
  2. 2.Center for the Neurobiology of Learning and Memory, U.C. Irvine 320 Qureshey Research LaboratoryUniversity of CaliforniaIrvineUSA

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