Download model of consciousne..

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the work of artificial intelligence, which forms the content of this project

Document related concepts

Nervous system network models wikipedia, lookup

Biological neuron model wikipedia, lookup

Development of the nervous system wikipedia, lookup

Metastability in the brain wikipedia, lookup

Convolutional neural network wikipedia, lookup

Philosophy of artificial intelligence wikipedia, lookup

Catastrophic interference wikipedia, lookup

Holonomic brain theory wikipedia, lookup

Neural engineering wikipedia, lookup

Types of artificial neural networks wikipedia, lookup

Recurrent neural network wikipedia, lookup

Neural correlates of consciousness wikipedia, lookup

Artificial neural network wikipedia, lookup

Unconscious mind wikipedia, lookup

Binding problem wikipedia, lookup

Neural binding wikipedia, lookup

Artificial consciousness wikipedia, lookup

Hard problem of consciousness wikipedia, lookup

Consciousness wikipedia, lookup

Animal consciousness wikipedia, lookup

Transcript
A model of Consciousness
With neural networks
By: Hadiseh Nowparast
Overview:
Neural Networks
The Global Workspace Theory
A hybrid neural network model for consciousness
About
neural networks
McCulloch-pitts model of a neuron:
A taxonomy of feed-forward & feed-back network architectures:
Applications:
The global workspace theory
 This theory provides a well-formalized model of
consciousness, identifying and describing the actors
that are involved in consciousness as well as their
interactions, roles and function.
 In this model, consciousness is part of a cognitive
distributed system.
 In order to regulate all the possible interactions, the
system needs atleast a bottleneck to force the modules
either to compete or to collaborate .
 In Baars’ model, the bottleneck is a working memory
(short-term memory) called the global workspace
which represents the consciousness.
A view of the main components of Baars’ model:
 Unconscious specialized processors
they represent a simple skill, a basic knowledge (e.g.,
the ability to make a simple addition, to understand a
sentence in our mother tongue, to perceive
temperature, etc.).
the processors are by definition unconscious as they
represent the set of competences of a given system.
 Consciousness or global workspace
when an unconscious specialized processors is unable
to achieve a given task by itself, it accesses the
consciousness that will in turn broadcast the needs of
the processors to the entire system.
 Coalition and conscious processes
the unconscious specialized processors that answer
the broadcasted needs form together with the
requesting processors a coalition able to achieve a
given task.
in turn, the coalition may need further skills; it will
then iteratively access the consciousness in order to
have the needs broadcasted to the system.
A so-formed coalition is called a conscious process.
 Contexts
they are the assumption of the system that restrain
access to the consciousness and discharge the
coalition formation process.
if the specialized processor wants to access
consciousness , it has either to fit the context or to wait
until the context is deactivated.
A hybrid neural network
model for consciousness
 This framework reflects explicit connection between
two parts of the brain:
• Global working memory
• Distributed modular cerebral networks relating to
specific brain functions
 This framework is composed of three layer :
• Physical mnemonic layer
• Abstract thinking layer
• Recognition layer
 Two first layers cooperate together through third layer to
accomplish information storage and cognition using
algorithms of how these interaction contribute to
consciousness:
•
the reception process whereby cerebral subsystems group
distributed signals into coherent object patterns.
• The partial recognition process whereby patterns from particular
subsystems are compared or stored as knowledge.
• The resonant learning process whereby global workspace stably
adjusts its structure to adapt to patterns’ changes.
This framework postulates that:
1. At any given time, many modular cerebral networks are
running in parallel and process data from outside in an
unconscious manner.
those networks belong to the physical mnemonic layer
of the framework.
an assumption is made about categorizing the outside
inputs into two groups: aware inputs and arousal input.
(the latter can only reach the recognition layer while the former can break
out of the recognition layer and take part in the associative recognition in
the global workspace.)
2. A recognition layer is a searching tree composed of
layered storage neurons positioned by the inherent
frequencies .
all feature of an object pattern are processed in the
lowest level by mnemonic layer networks before
entering here.
Some neurons in a particular level are grouped to form a
cluster. The representative of a cluster in the nth level
becomes a point in the higher-level n+1.
3. Global workspace that belongs to the abstract thinking
layer can potentially interconnect multiple cerebral
networks at the physical mnemonic layer through the
recognition layer.
when the global workspace is active for some duration,
the abstract information in the thinking layer is available
to variety of processes that would be mobilized by topdown intentional projection into cerebral actions that
may involve several distributed neural networks.
This global activity of abstract information through
workspace is defined as the conscious state of this
framework.
The general framework of consciousness:
References
 A hibrid neural network model for consciousness,2004
 A model of agent consciousness and its
implementation,2006
 Artificial neural networks: A tutorial
The end