A new representation and associated algorithms for generalized planning
Constructing plans that can handle multiple problem instances is a longstanding open problem in AI. We present a framework for generalized planning that captures the notion of algorithm-like plans and unifies various approaches developed for addressing this problem. Using this framework, and buildin...
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Veröffentlicht in: | Artificial intelligence 2011-02, Vol.175 (2), p.615-647 |
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container_title | Artificial intelligence |
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creator | Srivastava, Siddharth Immerman, Neil Zilberstein, Shlomo |
description | Constructing plans that can handle multiple problem instances is a longstanding open problem in AI. We present a framework for
generalized planning that captures the notion of algorithm-like plans and unifies various approaches developed for addressing this problem. Using this framework, and building on the TVLA system for static analysis of programs, we develop a novel approach for computing generalizations of classical plans by identifying sequences of actions that will make measurable progress when placed in a loop. In a wide class of problems that we characterize formally in the paper, these methods allow us to find generalized plans with loops for solving problem instances of unbounded sizes and also to determine the correctness and applicability of the computed generalized plans. We demonstrate the scope and scalability of the proposed approach on a wide range of planning problems. |
doi_str_mv | 10.1016/j.artint.2010.10.006 |
format | Article |
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subjects | Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Artificial intelligence Automated planning C (programming language) Computation Computer science control theory systems Computer systems and distributed systems. User interface Computer systems performance. Reliability Construction Exact sciences and technology Expert systems Handles Plan verification Plans with loops Representations Software Theoretical computing |
title | A new representation and associated algorithms for generalized planning |
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