Artificial Neural Nets Problem Solving Methods
Author(s) -
José Mira,
José R. Álvarez
Publication year - 2003
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
DOI - 10.1007/3-540-44869-1
Subject(s) - artificial neural network , computer science , artificial intelligence
This paper presents a neural design which is able to provide
the necessary reactive navigation and attention skills for 3D embodied
agents (virtual humanoids or characters). Based on Grossberg’s
neural model of conditioning [6], as recently implemented by Chang
and Gaudiando [7], and according to the Adaptative Resonance Theory
(ART) and the neuroscientific concepts associated, the neural design
introduced has been divided in two main phases. Firstly, an environmentcategorization
phase, where an on-line pattern recognition and categorization
of the current agent sensory input data is carried out by a self
organizing neural network, which will finally provide the agent’s short
term memory layer(STM). Secondly, and based on the classical conditioning
paradigm, the model will associate the interesting STM states,
from the navigation or attention points of view, to finally simulate these
necessary skills for 3D characters or humanoids. Finally, we will show
some experimental navigational results, through the integration of the
model presented in 3D virtual environments.Partially supported by the GVA-project CTIDIB-2002-182 (Spain)
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