| EPSRC Reference: |
GR/S30993/01 |
| Title: |
Stochastic Logic Programs for MCMC |
| Principal Investigator: |
Cussens, Dr J |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Computer Science |
| Organisation: |
University of York |
| Scheme: |
Standard Research (Pre-FEC) |
| Starts: |
01 September 2003 |
Ends: |
31 August 2005 |
Value (£): |
126,186
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| EPSRC Research Topic Classifications: |
| Artificial Intelligence |
Statistics & Appl. Probability |
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Summary on Grant Application Form |
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Interest in complex probabilistic models, and specifically those using a logical or relational framework, has been growing in the Artificial Intelligence community. This project applies one such approach: stochastic logic programs (SLPs). SLPs are parameterised logic programs which compactly and declaratively represent complex probability distributions. Lying at the intersection of statistics and logic programming, this project draws on theoretical and applied work from both disciplines. The project aims to implement an SLP environment for Bayesian inference using Markov chain Monte Carlo (MCMC). MCMC methods have greatly expanded the scope of Bayesian approaches, so that now it is possible, for example, to apply Bayesian approaches to (i) 'learning' the structure of graphical models and (ii) phylogenetic analysis. SLPs allow one to declare arbitrarily complex priors over, graphical models or phylogenetic trees in such a way that all the available prior knowledge ('hard' and 'soft') can be expressed and thus exploited.
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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.york.ac.uk |