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Cited by 1,112

The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.

Planning for conjunctive goals

Open access
Chapman, David·1987·Artificial Intelligence
DOI 10.1016/0004-3702(87)90092-0
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Abstract

Abstract The problem of achieving conjunctive goals has been central to domain-independent planning research; the nonlinear constraint-posting approach has been most successful. Previous planners of this type have been complicated, heuristic, and ill-defined. I have combined and distilled the state of the art into a simple, precise, implemented algorithm (TWEAK) which I have proved correct and complete. I analyze previous work on domain-independent conjunctive planning; in retrospect it becomes clear that all conjunctive planners, linear and nonlinear, work the same way. The efficiency and correctness of these planners depends on the traditional add/delete-list representation for actions, which drastically limits their usefulness. I present theorems that suggest that efficient general purpose planning with more expressive action representations is impossible, and suggest ways to avoid this problem.

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Metadata

Authors
Chapman, D.
Venue
Artificial Intelligence
Publisher
Elsevier BV
Published
1987-07
Volume
32
Issue
3
Pages
333-377
ISSN
0004-3702 (ISSN-L)
DOI
10.1016/0004-3702(87)90092-0
OpenAlex
W2171798962
Cited by
1,112
References
41
FWCI
53.87
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Planning for conjunctive goals. https://app.cochat.ai/papers/10.1016/0004-3702(87)90092-0
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Chapman, D. (1987). Planning for conjunctive goals. Artificial Intelligence. https://doi.org/10.1016/0004-3702(87)90092-0

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.