Discovery Projects - Grant ID: DP0210999

Funding Activity

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Funded Activity Summary

Asynchronous Continuous Time Conditioning. Methodology for reasoning about Asynchronous Temporal Conditional Events (ATCE) obtains, complete with logical calculus for causal relations, reasoning about continuous time belief change, and markov chain algorithms calculating joint distributions of ATCE's. Current techniques, including bayesian nets, are oblivious to temporal aspects; within our model they can be enhanced to recognize dynamic time changes. Ours is the first such unified model and first to link conditional objects with continuous time constraints. Need for structures we propose arises in diagnostic reasoning, bayesian learning, temporal databases, and time-dependent data mining. Several commercial products (like Microsoft Office Assistant)could apply them forthwith.

Funded Activity Details

Start Date: 08-02-2002

End Date: 31-12-2008

Funding Scheme: Discovery Projects

Funding Amount: $211,164.00

Funder: Australian Research Council