The PANDA Framework for Hierarchical Planning
| Autor: | Gregor Behnke, Daniel Höller, Pascal Bercher, Susanne Biundo |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
0209 industrial biotechnology
Planning & design Computer science business.industry Planung Perspective (graphical) 02 engineering and technology Plan (drawing) Space (commercial competition) Propositional calculus Input language 020901 industrial engineering & automation Artificial Intelligence Reachability ddc:000 DDC 620 / Engineering & allied operations 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Software system ddc:620 DDC 000 / Computer science information & general works Software engineering business Advice (complexity) |
| Zdroj: | KI - Künstliche Intelligenz. 35:391-396 |
| ISSN: | 1610-1987 0933-1875 |
| DOI: | 10.1007/s13218-020-00699-y |
| Popis: | During the last years, much progress has been made in hierarchical planning towards domain-independent systems that come with sophisticated techniques to solve planning problems instead of relying on advice in the input model. Several of these novel methods have been integrated into the PANDA framework, which is a software system to reason about hierarchical planning tasks. Besides solvers for planning problems based on plan space search, progression search, and translation to propositional logic, it also includes techniques for related problems like plan repair, plan and goal recognition, or plan verification. These various techniques share a common infrastructure, like e.g. a standard input language or components for grounding and reachability analysis. This article gives an overview over the PANDA framework, introduces the basic techniques from a high level perspective, and surveys the literature describing the diverse components in detail. publishedVersion |
| Databáze: | OpenAIRE |
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