cognition through imagination and affect murray shanahan imperial college london department of...
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Cognition Through Imagination and Affect
Murray ShanahanImperial College London
Department of Computing
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Overview
Brain-inspired architectures
Cognitively mediated action
An internal sensorimotor loop
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Brain-inspired ArchitecturesProgress towards the vision of human-level AI has been slow
Classical AI has not yet succeeded in devising systems that can match the common sense reasoning skills of a young child
Biologically-inspired AI has been very slow to move beyond trivial motor tasks and tackle the difficult questions of cognition
Some researchers are now turning to the human brain for inspiration, especially to architecture-level theories of its functioning
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A New VocabularyWe have a whole new set of concepts to explore
But all should be in scare quotes
Many are alien to both top-down classical AI and bottom-up biologically-inspired AI
“Imagination”
“Emotion”
“Consciousness”
Or, more technicallyInternally closed sensorimotor loops
Affect-based mechanisms of selection
Global workspaces
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Imagination and AffectHere we have an internally-closed sensorimotor loop that can simulate interaction with the environment
It rehearses trajectories through sensorimotor space without having to traverse those trajectories for real
The outcome of various potential trajectories can be evaluated. This where affect comes in
The result impacts on action selection
Motorcortex
Affect
WORLD
Inner sensorimotor loop(the “core circuit”)
Sensorycortex
ACa ACb
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Why an Internal Loop?The inner sensorimotor loop implements a form of analogical representation
The medium of representation has the same structure as what is being represented – eg: a map
We get spatial properties for free, and complex shapes can be represented
The dynamics of the inner loop has a close relationship to the dynamics of the outer loop
It can realise inner speech as well as mental imagery
Categories become attractors in a state space having same structure as that of sensory input
This addresses the symbol grounding problem
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A Cognitively-mediated ActionOn sight of green, turn-right is action has highest “salience”
But this reactive response is held on veto while turning right is rehearsed
Sight of red of predicted
But red is aversive
So salience of turn-right is modulated down, resulting in turn-left becoming the action with highest salience
Again this response is held on veto
Now sight of blue is predicted, and blue is associated with reward
So salience of turn-left is modulated up
Eventually it reaches a threshold, veto is released, and robot acts
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The Core Circuit
VC / IT = visual cortex / inferior temporal cortex
AC = association cortex
GW / BG = global workspace / basal ganglia
Am = amygdala
This “core circuit” combines an internal sensorimotor loop with mechanisms for broadcast and competition, and thereby marries the simulation
hypothesis with global workspace theory
GW / BG
AC1a
AC2a
AC3a
AC1b
AC2b
AC3b
VC / IT
Am
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Affect Circuitry (Am)
Reward
Punish
Salience1
Salience2
Salience3
VC / IT
GWBG
VC / IT = visual cortex / infero-temporal cortex, BG = basal ganglia,GW = global workspace
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Motor Circuitry
MC = motor cortex
BG = basal ganglia
Am = amygdala
MC1
MC2
MC3
BG
Veto
Selectedactionbuffer
Motorcommand
VC / IT
Am
Robotmotor
controllers
Newaction
detector
VC / IT
Urgency
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Concluding RemarksThe brain-inspired approach to building cognitive systems is promising
But it is still relatively unexplored
Affect plays a vital role in the proposed architecture
It is currently a simple scalar value. A vector of “basic emotions” would be interesting to investigate
The relationship to consciousness is very interesting
Too bad there’s no time to talk about it
Shanahan, M.P. (2006). A Cognitive Architecture that Combines Inner Rehearsal with a Global Workspace. Consciousness and Cognition 15, 433–449.