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prodigy/analogy: Analogical Reasoning in General Problem Solving
, 1994
"... This paper describes the integration of analogical reasoning into general problem solving as a method of learning at the strategy level to solve problems more effectively. The method based on derivational analogy has been fully implemented in prodigy/analogy and proven empirically to be amenable t ..."
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Cited by 174 (20 self)
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This paper describes the integration of analogical reasoning into general problem solving as a method of learning at the strategy level to solve problems more effectively. The method based on derivational analogy has been fully implemented in prodigy/analogy and proven empirically to be amenable to scaling up both in terms of domain and problem complexity. prodigy/analogy addresses a set of challenging problems, namely: how to accumulate episodic problem solving experience, cases, how to define and decide when two problem solving situations are similar, how to organize a large library of planning cases so that it may be efficiently retrieved, and finally how to successfully transfer chains of problem solving decisions from past experience to new problem solving situations when only a partial match exists among corresponding problems. The paper discusses the generation and replay of the problem solving cases and we illustrate the algorithms with examples. We present briefly the librar...
Planning by Rewriting: Efficiently Generating High-Quality Plans
- In Proceedings of the Fourteenth National Conference on Artificial Intelligence
, 1997
"... Domain-independent planning is a hard combinatorial problem. Taking into account plan quality makes the task even more difficult. We introduce a new paradigm for efficient high-quality planning that exploits plan rewriting rules and efficient local search techniques to transform an easy-to-generate, ..."
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Cited by 60 (12 self)
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Domain-independent planning is a hard combinatorial problem. Taking into account plan quality makes the task even more difficult. We introduce a new paradigm for efficient high-quality planning that exploits plan rewriting rules and efficient local search techniques to transform an easy-to-generate, but possibly suboptimal, initial plan into a low-cost plan. In addition to addressing the issues of efficiency and quality, this framework yields a new anytime planning algorithm. We have implemented this planner and applied it to several existing domains. The results show that this approach provides significant savings in planning effort while generating high-quality plans. Introduction Planning is the process of generating a network of actions that achieves a desired goal from an initial state of the world. Domain independent planning accepts as input, not only the initial state and the goal, but also the domain specification (i.e., the operators). This is a problem of considerable prac...
Building and Refining Abstract Planning Cases by Change of Representation Language
- Journal of Artificial Intelligence Research
, 1995
"... Planning Cases by Change of Representation Language Ralph Bergmann bergmann@informatik.uni-kl.de Wolfgang Wilke wilke@informatik.uni-kl.de Centre for Learning Systems and Applications (LSA) University of Kaiserslautern, P.O.-Box 3049, D-67653 Kaiserslautern, Germany Abstract Abstraction is one of ..."
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Cited by 57 (7 self)
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Planning Cases by Change of Representation Language Ralph Bergmann bergmann@informatik.uni-kl.de Wolfgang Wilke wilke@informatik.uni-kl.de Centre for Learning Systems and Applications (LSA) University of Kaiserslautern, P.O.-Box 3049, D-67653 Kaiserslautern, Germany Abstract Abstraction is one of the most promising approaches to improve the performance of problem solvers. In several domains abstraction by dropping sentences of a domain description -- as used in most hierarchical planners -- has proven useful. In this paper we present examples which illustrate significant drawbacks of abstraction by dropping sentences. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract. However, to achieve a powerful change of th...
PARIS: Flexible Plan Adaptation by Abstraction and Refinement
- Proceedings of the Workshop on Adaptation in Case-Based Reasoning, th European Conference on Artificial Intelligence
"... ion and Refinement Ralph Bergmann and Wolfgang Wilke Centre for Learning Systems and Applications (LSA) University of Kaiserslautern Dept. of Computer Science P.O.-Box 3049, D-67653 Kaiserslautern, Germany e-mail: bergmann@informatik.uni-kl.de 1 Introducion Paris (Plan Abstraction and Refinement i ..."
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Cited by 13 (1 self)
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ion and Refinement Ralph Bergmann and Wolfgang Wilke Centre for Learning Systems and Applications (LSA) University of Kaiserslautern Dept. of Computer Science P.O.-Box 3049, D-67653 Kaiserslautern, Germany e-mail: bergmann@informatik.uni-kl.de 1 Introducion Paris (Plan Abstraction and Refinement in an Integrated System) [4, 2] is a domain independent case-based planning system which allows the flexible reuse of planning cases by abstraction and refinement. This approach is mainly inspired by the observation that reuse of plans must not be restricted to a single description level. In domains with a high variation in the problems, the reuse of past solutions must be achieved at various levels of abstraction. In Paris, planning cases given at the concrete level are abstracted to several levels of abstraction which leads to a set of abstract cases that are stored in the case-base. This case abstraction is done automatically in the retain phase of the CBR-process modell [1]. When a new pr...
Adaptation Versus Retrieval Trade-Off Revisited: an Analysis of Boundary Conditions
"... Abstract. In this paper we revisit the trade-off between adaptation and retrieval effort traditionally held as a principle in case-based reasoning. This principle states that the time needed for adaptation reduces with the time spent searching for an adequate case to be retrieved. In particular, if ..."
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Cited by 4 (1 self)
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Abstract. In this paper we revisit the trade-off between adaptation and retrieval effort traditionally held as a principle in case-based reasoning. This principle states that the time needed for adaptation reduces with the time spent searching for an adequate case to be retrieved. In particular, if very little time is spent in retrieval, the adaptation effort will be high. Correspondingly, if the retrieval effort is high, the adaption effort is low. We analyzed this principle in two boundary conditions: (1) when very bad and (2) when highly capable adaptation procedures are used. We conclude that in the first boundary condition the adaptation-retrieval trade-off does not necessarily exist. We also claim that the second does not hold for a class of planning domains frequently used in the literature. To validate this claim, we performed experiments on two domains of this type.
Feature Weighting by Explaining Case-Based Problem Solving Episodes
, 1996
"... We present a similarity criterion based on feature weighting. Feature weights are recomputed dynamically according to the performance of cases during problem solving episodes. We will also present a novel algorithm to analyze and explain the performance of the retrieved cases and to determine the fe ..."
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Cited by 2 (0 self)
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We present a similarity criterion based on feature weighting. Feature weights are recomputed dynamically according to the performance of cases during problem solving episodes. We will also present a novel algorithm to analyze and explain the performance of the retrieved cases and to determine the features whose weights need to be recomputed. We will perform experiments and show that the integration in a feature weighting model of our similarity criterion with our analysis algorithm improves the adaptability of the retrieved cases by converging to best weights for the features over a period of multiple problem solving episodes. 1 Introduction An essential factor influencing the effectiveness of case-based problem solving is the retrieval phase (Aamodt and Plaza, 1994). In the context of planning and design, retrieval means searching for adaptable cases (Smyth and Keane, 1994; Marir and Watson, 1995; Smyth and Keane, 1995). Thus, any similarity criterion should measure the adaptation ef...
User Interface
, 1997
"... The PRODIGY user interface supports the process of both building and running a planning domain in PRODIGY. It was designed to be highly modular, requiring no changes to the code of the PRODIGY planner to run, and extensible, so that interfaces to other modules built on PRODIGY could easily be integr ..."
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Cited by 1 (1 self)
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The PRODIGY user interface supports the process of both building and running a planning domain in PRODIGY. It was designed to be highly modular, requiring no changes to the code of the PRODIGY planner to run, and extensible, so that interfaces to other modules built on PRODIGY could easily be integrated into the interface. In this paper we describe how these goals were achieved. We demonstrate building a domain and animating the planning process. We describe extensions to the user interface to support planning by analogical reasoning and probabilistic planning with PRODIGY. 1 On leave from Escola Federal de Engenharia de Itajuba, MG, Brazil. Visiting researcher at CMU with financial support provided byCNPq - Conselho Nacional de Desenvolvimento Cientfico e Tecnologico, Braslia, DF. 1 Introduction PRODIGY is a domain-independent planning and learning system that provides a base planning module and many capabilities implemented as integrated modules [Veloso et al., 1995] . We recentl...
Recommended Citation Lee-Urban, Stephen Montgomery, "Hierarchical Planning Knowledge for Refining Partial-Order Plans " (2012). Theses and Dissertations. Paper 1213. Hierarchical Planning Knowledge for Refining Partial-Order Plans
, 2012
"... Lehigh University ..."
Flexible Reuse of Plans by Abstraction and Refinement
"... ion and Refinement Ralph Bergmann and Wolfgang Wilke e-mail: bergmann@informatik.uni-kl.de Centre for Learning Systems and Applications University of Kaiserslautern Dept. of Computer Science P.O.-Box 3049, D-67653 Kaiserslautern, Germany Abstract In this paper we present an approach to the flexib ..."
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ion and Refinement Ralph Bergmann and Wolfgang Wilke e-mail: bergmann@informatik.uni-kl.de Centre for Learning Systems and Applications University of Kaiserslautern Dept. of Computer Science P.O.-Box 3049, D-67653 Kaiserslautern, Germany Abstract In this paper we present an approach to the flexible reuse of planning cases by abstraction and refinement. A new abstraction methodology is described in detail and related algorithms for automatically building and refining abstract planning cases are sketched. Based on a given concrete and abstract language together with a generic abstraction theory, this abstraction approach allows to change the whole representation of a planning case from a concrete to abstract. 1 Introduction In this paper we present an approach to the flexible reuse of planning cases by abstraction and refinement. This approach is mainly inspired by the observation that reuse of plans must not be restricted to a single level of description. In domains in which th...
Plan Abstraction with Change of Representation Language
"... ion with Change of Representation Language Ralph Bergmann e-mail: bergmann@informatik.uni-kl.de Centre for Learning Systems and Applications University of Kaiserslautern Dept. of Computer Science P.O.-Box 3049, D-67653 Kaiserslautern, Germany Abstract Abstraction is one of the most promising appr ..."
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ion with Change of Representation Language Ralph Bergmann e-mail: bergmann@informatik.uni-kl.de Centre for Learning Systems and Applications University of Kaiserslautern Dept. of Computer Science P.O.-Box 3049, D-67653 Kaiserslautern, Germany Abstract Abstraction is one of the most promising approaches to improve the performance of problem solvers. Abstraction by dropping sentences of a domain description -- as used in most hierarchical planners -- is known to be very representation dependent. To overcome these drawbacks, we propose a more general view of abstraction involving the change of representation language. We have developed a new abstraction methodology and a related sound and complete learning algorithm that allows the complete change of representation language of planning cases from concrete to abstract. 1 Introduction Abstraction is one of the most challenging and also promising approaches to improve complex problem solving and it is inspired by the way how humans see...
