PLOW: A Collaborative Task Learning Agent
Describes PLOW, which learns executable web-task models from a session combining demonstrations, natural-language explanations, and dialogue. Browser instrumentation connects user actions with DOM structure to support task generalization.
AI-assisted editorial review against a primary source. This is a catalog annotation, not an independent reproduction or endorsement.
What is this resource?
- Resource type
- Research papers
- Environment
- web
- Topics
- web-navigation, human-in-the-loop, planning
- Record publication date
- 2007
- Evidence retrieved
- 2026-10-17T09:53:26Z
- Resource ID
- url:628b5251757bb3888e89
Authors
James Allen, Nathanael Chambers, George Ferguson, Lucian Galescu, Hyuckchul Jung, Mary Swift, William Taysom
Cite this paper
Download BibTeX · Download CSL JSON
Citations preserve the selected source edition, its authors and recorded date precision. Unrecorded venues and identifiers are omitted.
Publication record
- Title
- PLOW: A Collaborative Task Learning Agent
- Authors
- James Allen, Nathanael Chambers, George Ferguson, Lucian Galescu, Hyuckchul Jung, Mary Swift, William Taysom
- Publication date (recorded precision)
- 2007
- Venue
- Twenty-Second AAAI National Conference on Artificial Intelligence
- Pages
- 1514-1519
Publication source ↗ · Publisher or author PDF ↗
Publication BibTeX · Publication CSL JSON
Date source: Supplied year precision: 2007. Papers section: AAAI-2007
Source notes: The ordered names follow the original published paper, without expanding initials or replacing names from secondary indexes. DOI and volume number are not supplied in the retained primary sources. No exact publication month/day is established.
Explore related topics
Scope and limitations
The annotation was reviewed against retained primary publication sources. Experiments have not been independently reproduced. The ordered names follow the original published paper, without expanding initials or replacing names from secondary indexes.
Primary evidence and verification
Source retrieval is separate from experiment reproduction. Use the original publication or publisher page when citing claims about the resource.
- editorial primary review
Retrieved 2026-10-17T09:53:26Z. Supports: details.publication.authors, details.publication.identity_basis, details.publication.notes, details.publication.pages, details.publication.pdf_url, details.publication.title, details.publication.url.
Content fingerprint
795d275c9f85180561fd101652221d30fb98daca2c2a00faf2b57c397bdfd68d - editorial primary review
Retrieved 2026-10-17T09:53:24Z. Supports: details.publication.date_basis, details.publication.date_parts, details.publication.notes, details.publication.type, details.publication.venue.
Content fingerprint
c0b3571efd5f2e137e42b38107de29aca6668819bec84109912d514867d85b8c - editorial primary review
Retrieved 2026-10-17T09:53:26Z. Supports: details.publication.authors, details.publication.identity_basis, details.publication.notes, details.publication.pages, details.publication.pdf_url, details.publication.title, details.publication.url, environments, name, scope, summary, topics.
Content fingerprint
795d275c9f85180561fd101652221d30fb98daca2c2a00faf2b57c397bdfd68d - editorial primary review
Retrieved 2026-10-17T09:53:24Z. Supports: details.publication.date_basis, details.publication.date_parts, details.publication.notes, details.publication.type, details.publication.venue, environments, kind.
Content fingerprint
c0b3571efd5f2e137e42b38107de29aca6668819bec84109912d514867d85b8c
Suggest a correction
Open a source-backed correction. Include this record ID and the original source. Read our editorial policy and coverage boundaries.