Learning plan abstractions

Bergmann, Ralph

doi:10.1007/bfb0019004

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…In [1] is introduced the abstraction and respecialization approach to adaptation that consists in (1) abstracting the solution Sol(srce) of srce into a solution Sol(A) of an abstract problem A, and (2) specializing Sol(A) in order to solve tgt. According to [15], this adaptation can be better qualified as a generalization/specialization approach (versus an abstraction/refinement approach), but this distinction is not made in [1]. The examples of conservative adaptations presented in this paper may be seen as the application of some generalization and specialization adaptations.…”

Section: Discussionmentioning

confidence: 99%

Application of the Revision Theory to Adaptation in Case-Based Reasoning: The Conservative Adaptation

Lieber

Case-Based Reasoning Research and Development

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Abstract. Case-based reasoning aims at solving a problem by the adaptation of the solution of an already solved problem that has been retrieved in a case base. This paper defines an approach to adaptation called conservative adaptation; it consists in keeping as much as possible from the solution to be adapted, while being consistent with the domain knowledge. This idea can be related to the theory of revision: the revision of an old knowledge base by a new one consists in making a minimal change on the former, while being consistent with the latter. This leads to a formalization of conservative adaptation based on a revision operator in propositional logic. Then, this theory of conservative adaptation is confronted to an application of case-based decision support to oncology: a problem of this application is the description of a patient ill with breast cancer, and a solution, the therapeutic recommendation for this patient. Examples of adaptations that have actually been performed by experts and that can be captured by conservative adaptation are presented. These examples show a way of adapting contraindicated treatment recommendations and treatment recommendations that cannot be applied.

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Section: Discussionmentioning

confidence: 99%

Application of the Revision Theory to Adaptation in Case-Based Reasoning: The Conservative Adaptation

Lieber

Case-Based Reasoning Research and Development

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“…We now present the Pabs algorithm (Bergmann, 1992c;Wilke, 1993) for automatically learning a set of abstract cases from a given concrete case. Thereby, we assume that a concrete domain D c and an abstract domain D a are given together with a generic abstraction theory A.…”

Section: Computing Case Abstractionsmentioning

confidence: 99%

“…The problem of case abstraction can now be described as transforming a case from the concrete domain D c into a case in the abstract domain D a (see Figure 7). This transformation will now be formally decomposed into two independent mappings: a state abstraction mapping , and a sequence abstraction mapping (Bergmann, 1992c). The state abstraction mapping transforms a selection of concrete state descriptions that occur in the solution to a problem into abstract state descriptions, 8.…”

Section: A Formal Model Of Case Abstractionmentioning

confidence: 99%

Building and Refining Abstract Planning Cases by Change of Representation Language

Bergmann¹,

Wilke²

1995

jair

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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 signi cant 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 the representation language, the abstract language itself as well as rules which describe admissible ways of abstracting states must be provided in the domain model.This new abstraction approach is the core of Paris (Plan Abstraction and Re nement in an Integrated System), a system in which abstract planning cases are automatically learned from given concrete cases. An empirical study in the domain of process planning in mechanical engineering shows signi cant advantages of the proposed reasoning from abstract cases over classical hierarchical planning.1. Only Tenenberg's (1988) abstraction by analogical mappings and the planning system Sipe (Wilkins, 1988) contains rst approaches that allow a change of representation language.2. However, we might assume that the term X + 1 is modeled as a separate predicate in the precondition.Unfortunately, this does not change the described situation at all. 3. Because we assume many other operators besides the inc-operator, b 1 holds.

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Learning abstract planning cases

Bergmann

Wilke

1995

Lecture Notes in Computer Science

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Learning plan abstractions

Cited by 5 publications

References 15 publications

Application of the Revision Theory to Adaptation in Case-Based Reasoning: The Conservative Adaptation

Application of the Revision Theory to Adaptation in Case-Based Reasoning: The Conservative Adaptation

Building and Refining Abstract Planning Cases by Change of Representation Language

Learning abstract planning cases

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