Data processing: artificial intelligence – Neural network – Learning task
Reexamination Certificate
2006-05-18
2008-08-19
Holmes, Michael B (Department: 2129)
Data processing: artificial intelligence
Neural network
Learning task
Reexamination Certificate
active
07415444
ABSTRACT:
Systems and methods for solving a constraint satisfaction problem (CSP) defined by one or more variables, constraints and probabilistic requests (PRs) are provided. In one embodiment, each PR is mapped onto a set of constraints that implement the PR. The CSP solver then finds a series of solutions to the CSP. For each solution, if a constraint associated with a PR is satisfied, then a success counter for that PR is incremented; else a failure counter for that PR is incremented. If the constraint was not considered for the purpose of solving the CSP, then the failure counter for the PR associated with the constraint is incremented.
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Copty Shady
Emek Roy
Jaeger Itai
Katz Yoav
Lubliner Shai
Holmes Michael B
International Business Machines - Corporation
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