Bart Peintner

dblp:32/824 · DBLP profile ↗
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9ranked-venue papers
4as first author
0since 2021 · last 2017
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 7 · 4 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 2 first-authorSoftware engineering, systems software and programming languages · 2 · 1 first-authorDatabases, data management, data science and information retrieval · 2Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
3 papers
Knowledge representation and reasoning · 66% Planning, search and constraint satisfaction · 34%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning › temporal reasoning
disjunctive temporal problem
0.122005
Augmenting Disjunctive Temporal Problems with Finite-Domain Constraints · AAAI 2005
Low-cost Addition of Preferences to DTPs and TCSPs · AAAI 2004
Knowledge, reasoning and agents › Knowledge representation and reasoning
temporal reasoning
0.122005
Augmenting Disjunctive Temporal Problems with Finite-Domain Constraints · AAAI 2005
Low-cost Addition of Preferences to DTPs and TCSPs · AAAI 2004
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › heuristic search
anytime search
0.112005
Anytime, Complete Algorithm for Finding Utilitarian Optimal Solutions to STPPs · AAAI 2005
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
temporal planning
0.112005
Anytime, Complete Algorithm for Finding Utilitarian Optimal Solutions to STPPs · AAAI 2005
Knowledge, reasoning and agents › Knowledge representation and reasoning › nonmonotonic reasoning
preference handling
0.012004
Low-cost Addition of Preferences to DTPs and TCSPs · AAAI 2004
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
soft constraints
0.012004
Low-cost Addition of Preferences to DTPs and TCSPs · AAAI 2004
Knowledge, reasoning and agents › Knowledge representation and reasoning › temporal reasoning
temporal constraint satisfaction
0.012004
Low-cost Addition of Preferences to DTPs and TCSPs · AAAI 2004

Methods — techniques the papers use, named apart from their topics

dynamic programming · 0.1branch-and-bound · 0.1constraint satisfaction · 0.0
YearPublicationVenuePosition
2017 Evaluating intelligent knowledge systems: experiences with a user-adaptive assistant agent
Pauline M. Berry, Thierry Donneau-Golencer, Khang Duong, Melinda T. Gervasio, Bart Peintner, Neil Yorke-Smith
Knowl. Inf. Syst.5
2011 PTIME: Personalized assistance for calendaring
abstract
In a world of electronic calendars, the prospect of intelligent, personalized time management assistance seems a plausible and desirable application of AI. PTIME ( Personalized Time Management ) is a learning cognitive assistant agent that helps users handle email meeting requests, reserve venues, and schedule events. PTIME is designed to unobtrusively learn scheduling preferences, adapting to its user over time. The agent allows its user to flexibly express requirements for new meetings, as they would to an assistant. It interfaces with commercial enterprise calendaring platforms, and it operates seamlessly with users who do not have PTIME. This article overviews the system design and describes the models and technical advances required to satisfy the competing needs of preference modeling and elicitation, constraint reasoning, and machine learning. We further report on a multifaceted evaluation of the perceived usefulness of the system.
Pauline M. Berry, Melinda T. Gervasio, Bart Peintner, Neil Yorke-Smith
ACM Trans. Intell. Syst. Technol.3
2009 Evaluating User-Adaptive Systems: Lessons from Experiences with a Personalized Meeting Scheduling Assistant
Pauline M. Berry, Thierry Donneau-Golencer, Khang Duong, Melinda T. Gervasio, Bart Peintner, Neil Yorke-Smith
IAAI5
2009 Task Assistant: Personalized Task Management for Military Environments
Bart Peintner, Jason Dinger, Andres C. Rodriguez, Karen L. Myers
IAAI1
2007 Strong Controllability of Disjunctive Temporal Problems with Uncertainty
Bart Peintner, K. Brent Venable, Neil Yorke-Smith
CP1
2005 Augmenting Disjunctive Temporal Problems with Finite-Domain Constraints
Michael D. Moffitt, Bart Peintner, Martha E. Pollack
AAAI2
2005 Anytime, Complete Algorithm for Finding Utilitarian Optimal Solutions to STPPs
Bart Peintner, Martha E. Pollack
AAAI1
2005 On Solving Soft Temporal Constraints Using SAT Techniques
Hossein M. Sheini, Bart Peintner, Karem A. Sakallah, Martha E. Pollack
CP2
2004 Low-cost Addition of Preferences to DTPs and TCSPs
Bart Peintner, Martha E. Pollack
AAAI1