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EPSRC Reference: GR/S47946/01
Title: Machine consciousness through internal modelling
Principal Investigator: Holland, Professor O
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Computer Sci and Electronic Engineering
Organisation: University of Essex
Scheme: Standard Research (Pre-FEC)
Starts: 01 April 2004 Ends: 31 July 2007 Value (£): 314,781
EPSRC Research Topic Classifications:
Artificial Intelligence Cognitive Science Appl. in ICT
Image & Vision Computing
EPSRC Industrial Sector Classifications:
Information Technologies
Related Grants:
GR/S47953/01
Panel History:  
Summary on Grant Application Form
This adventurous project is an attempt to build a conscious machine. A transdisciplinary team of roboticists, computer scientists, and neuropsychologists from the Universities of Essex and Bristol will design and construct a series of increasingly complex biologically inspired autonomous mobile robots forced to survive in a series of progressively more difficult environments, and will then study the external and internal behaviour of the robots, looking for signs and characteristics of consciousness. The key idea is that, in order to survive, each robot will have to plan its actions, and to do so effectively it will have to build and make use of two kinds of internal models: a model of the world in which it finds itself, and a model of itself - its body, its sensors, its manipulators, its preferences, its history, and so on. The robots will gain most of their information about the world by vision systems closely modelled on those of humans and other primates; many of the internal processes and models used by the robots will therefore be based on vision, and will be accessible to the investigating team as visual displays. The main focus of interest will be the self-model; its characteristics and internal changes are expected to resemble those of the conscious self in humans, perhaps closely enough to enable some of the robots to be regarded as possessing a form of machine consciousness.
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Organisation Website: http://www.sx.ac.uk