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Contextual Learning in the Neurosolver
Author(s) -
Andrzej Bieszczad,
Kasia M. Bieszczad
Publication year - 2006
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-38625-4
DOI - 10.1007/11840817_50
Subject(s) - computer science , planner , neuromorphic engineering , architecture , context (archaeology) , artificial intelligence , human–computer interaction , artificial neural network , art , paleontology , visual arts , biology
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.

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