Program synthesis for generalized planning
Generalized planning is the problem of finding an algorithm-like solution called generalized plan to multiple planning instances. The two main tasks to perform in generalized planning are synthesizing and validating generalized plans. In this thesis, we represent generalized plans as a planning prog...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/663753 |
| Acceso en línea: | http://hdl.handle.net/10803/663753 |
| Access Level: | acceso abierto |
| Palabra clave: | Classical planning Generalized planning Automated programming Program synthesis 62 |
| Sumario: | Generalized planning is the problem of finding an algorithm-like solution called generalized plan to multiple planning instances. The two main tasks to perform in generalized planning are synthesizing and validating generalized plans. In this thesis, we represent generalized plans as a planning programs, enhanced with conditional goto conditions, or finite state controllers. Then, we compile generalized planning problems to PDDL such that we can compute programs using off-the-shelf classical planners. Because solutions to generalized planning are similar to algorithms, we can build libraries of previous knowledge and reuse them if necessary using a call stack. This feature extends to planning programs with procedures, hierarchical finite state controllers and allows recursion. Finally, we introduce new application areas for planning, e.g. unsupervised classification of instances or context-free grammar generation, by defining non-deterministic choice functions for planning programs. |
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