| EPSRC Reference: |
GR/T08753/01 |
| Title: |
AIBACS: Rapid insect-like visual learning algorithms |
| Principal Investigator: |
Collett, Professor T |
| Other Investigators: |
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| Researcher Co-Investigators: |
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| Project Partners: |
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| Department: |
Biology and Environmental Science |
| Organisation: |
University of Sussex |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 January 2005 |
Ends: |
31 December 2007 |
Value (£): |
530,977
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Biomedical neuroscience |
| Image & Vision Computing |
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| EPSRC Industrial Sector Classifications: |
| No relevance to Underpinning Sectors |
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| Panel History: |
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Summary on Grant Application Form |
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In marked contrast to current artificial systems, navigating insects learn complex visual sequences in remarkably few trials. An important part of this ability is the use of innate behaviours to structure and guide the learning process. Given their relatively small neural resources, insects have good reason to place a premium on finding such simplifying strategies. Enough is now known about these behavioural strategies to attempt a formal understanding of this type of learning. The central aim of this proposal is to provide such an understanding using detailed information theoretic analyses of data acquired during insect and robotic studies. This will inform the design of novel learning algorithms, to be demonstrated in vision-based navigation and other sequential learning application, as well as the development of more general principles for the design and understanding of adaptive systems.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.sussex.ac.uk |