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Tutorial: Retargeting
contact: seantrott@icsi.berkeley.edu
In general, we believe that retargeting the application to a new application consists of several crucial steps:
- Identify application domain and its relevant vocabulary, as well as the API; if the API doesn't exist, define/design it.
- Design n-tuple templates to convey semantics to Problem Solver.
- Add relevant tokens (and schemas/constructions, if necessary) to the grammar with the Token Tool.
- Extend existing Core Specializer and Problem Solver as needed for application.
- Build and test the new product.
Below are two hypothetical examples of retargeting. One is for an imagined "cooking" robot, and the other is for a system that makes predictions about economic states and policies based on metaphors in language.
KARMA (Naryanan, 1997) was a system that made predictions about economic states and policies based on metaphors in language. The original project did not include a module for language analysis, however, and assumed as input an ntuple-like feature-structure.
We considered how one would integrate a working KARMA system with our system, and came up with the steps below.
- Identify application domain and its relevant vocabulary, as well as the API; if the API doesn't exist, define/design it.
Domain: Economic policy metaphors Vocabulary: Source: MOTION (stumble, collapse...) HEALTH (cure, prescribe, sick ...) TARGET: ECONOMIC POLICY (economy, depression..) App: (after) KARMA