Garforth, Jason P.
(2006).
Executive attention, action selection and attention-based learning in neurally controlled autonomous agents.
PhD thesis,
The Open University.
Full text available as:
Abstract
I describe the design and implementation of an integrated neural architecture, modelled on human executive attention, which is used to control both automatic (reactive) and willed action selection in a simulated robot. The model, based upon Norman and Shallice's supervisory attention system, incorporates important features of human attentional control: selection of an intended task over a more salient automatic task; priming of future tasks that are anticipated; and appropriate levels of persistence of focus of attention. Recognising that attention-based learning, mediated by the limbic system, and the hippocampus in particular, plays an important role in adaptive learning, I extend the Norman and Shallice model, introducing an intrinsic, attention-based learning mechanism that enhances the automaticity of willed actions and reduces future need for attentional effort required for dealing with distractions. These enhanced features support a new level of attentional autonomy in the operation of the simulated robot. Some properties of the model are explored using lesion studies, leading to the identification of a correspondence between the behavioural pathologies of the simulated robot and those seen in human patients suffering dysfunction of executive attention.
| Item Type: |
Thesis
(PhD)
|
| Copyright Holders: |
2006 Jason P. Garforth |
| Keywords: |
executive attention; action selection; autonomous robotics; cognitive robotics; adaptive learning; neural network |
| Academic Unit/Department: |
Social Sciences > Sociology |
| Item ID: |
22333 |
| Depositing User: |
Anthony Meehan
|
| Date Deposited: |
14 Apr 2011 14:52 |
| Last Modified: |
14 Apr 2011 21:41 |
| URI: |
http://oro.open.ac.uk/id/eprint/22333 |
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