Download Behaviour Based Knowledge Systems

Aims to bridge the gap between
behaviour and knowledge based
systems.
 Implications for understanding of
emergence of cognitive intelligence
 Also holds implications for the
application of these methods in future
systems.
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Vegetative – by default in order to live.
Reflex – simple immediate reaction to
stimuli
Reactive – more complex reaction to stimuli
Motivated – Dependent on external stimuli
and internal motivations
Reasoned – Manipulation of abstract
concepts
Conscious – Anything higher, too complex
to be modelled by the methods proposed
Problem – How to abstract perception of
world for manipulation and reasoning?
 Generalization of perceptions or other
concepts
 Concepts learned from patterns and
regularities
 Concepts reinforced with experience
 Concepts are unique to the individual as
experiences differ
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1. concept abstraction
 2. grounding of concepts though action
 3. sharing of concepts through social
interactions (language)
 4. manipulation of concepts (logic)
 5. evolution of concepts (culture)
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BBKS are necessarily simplifications of
natural systems
 Not going to produce convincing
imitations of natural intelligence
 More detailed analysis is described in
subsequent papers
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The paper itself is quite general
 Of interest as a means of understanding
emergence of knowledge
 Limited potential as a means of
producing intelligent systems
 Nature has already produced
intelligence so it makes sense to learn
from it
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The website relating to Gershenson’s work on BBKS including
virtual lab http://turing.iimas.unam.mx/~cgg/cogs/keb/
His current website at the Universidad Nacional Autónoma de
México http://turing.iimas.unam.mx/~cgg/
Questions?