Title: Cognition Through Imagination and Affect
1Cognition Through Imagination and Affect
- Murray Shanahan
- Imperial College London
- Department of Computing
2Overview
- Brain-inspired architectures
- Cognitively mediated action
- An internal sensorimotor loop
3Brain-inspired Architectures
- Progress 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
4A New Vocabulary
- We 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 technically
- Internally closed sensorimotor loops
- Affect-based mechanisms of selection
- Global workspaces
5Imagination and Affect
- Here 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
6Why 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
7A Cognitively-mediated Action
- On 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
8The 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
9Affect Circuitry (Am)
VC / IT visual cortex / infero-temporal cortex,
BG basal ganglia, GW global workspace
10Motor Circuitry
MC motor cortex BG basal ganglia Am
amygdala
11Concluding Remarks
- The 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 theres 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,
433449.