Demo Data from EDBT 2026 / reviewers in the wild / expert
Alice M. Mulvehill
dblp:17/6332 · also Alice Mulvehill
· DBLP profile ↗
7ranked-venue papers
3as first author
0since 2021 · last 2020
0000-0003-2981-0675ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 5 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-authorDatabases, data management, data science and information retrieval · 1Human-computer interaction and ubiquitous computing · 1 · 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
2 papers |
Planning, search and constraint satisfaction · 56% Knowledge representation and reasoning · 39% Multi-agent systems · 5% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › hierarchical planning
hierarchical task network |
0.2 | 1 | 2013 | Temporal Milestones in HTNs · AAAI 2013 |
Knowledge, reasoning and agents › Knowledge representation and reasoning
temporal reasoning |
0.2 | 1 | 2013 | Temporal Milestones in HTNs · AAAI 2013 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › plan execution
plan execution monitoring |
0.1 | 1 | 2007 | Expectation Failure as a Basis for Agent-Based Model Diagnosis and Mixed Initiative Model Adaptation during Anomalous Plan Execution · IJCAI 2007 |
Knowledge, reasoning and agents › Multi-agent systems
agent-based simulation |
0.0 | 1 | 2007 | Expectation Failure as a Basis for Agent-Based Model Diagnosis and Mixed Initiative Model Adaptation during Anomalous Plan Execution · IJCAI 2007 |
Methods — techniques the papers use, named apart from their topics
landmark variables · 0.2hierarchical task networks · 0.2mixed-initiative adaptation · 0.1agent-based model diagnosis · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | A Semantic Framework for Enabling Radio Spectrum Policy Management and Evaluation
Henrique Santos 0002, Alice M. Mulvehill, John S. Erickson, Jamie P. McCusker, Minor Gordon, Owen Xie, Samuel Stouffer, Gerard Capraro, Alex Pidwerbetsky, John Burgess, Allan Berlinsky, Kurt A. Turck, Jonathan D. Ashdown, Deborah L. McGuinness |
ISWC (2) | 2 |
| 2013 | Temporal Milestones in HTNsabstractWe present temporal milestones for hierarchical task networks to enable the complex synchronization of tasks. A temporal milestone of a task is an intermediate event that occurs during the execution of a complex task, e.g., the start time, the end time or a milestone of any of its subtasks. Unlike landmark variables, introduced in existing work, temporal milestones respect the task abstraction boundaries and preserve structural properties enabling much more efficient reasoning. Furthermore, temporal milestones are as expressive as landmark variables. We provide analytical and empirical evidence to support these claims. Fusun Yaman, Brett Benyo, Alice M. Mulvehill |
AAAI | 3 |
| 2013 | Leveraging Historical Experience to Evaluate and Adapt Courses of Action
Alice M. Mulvehill, Brett Benyo, Fusun Yaman |
ICCBR | 1 |
| 2007 | Expectation Failure as a Basis for Agent-Based Model Diagnosis and Mixed Initiative Model Adaptation during Anomalous Plan Execution
Alice M. Mulvehill, Brett Benyo, Michael T. Cox, Renu Kurien Bostwick |
IJCAI | 1 |
| 1997 | ForMAT and Parka: A Technology Integration Experiment and Beyond
David Rager, James A. Hendler, Alice M. Mulvehill |
ICCBR | 3 |
| 1994 | Case-Based Reasoning Applied to A Force Generation Decision Aid
Stephen E. Cross, Donald F. Roberts, Alice M. Mulvehill, J. Allen Sears |
ISMIS | 3 |
| 1988 | A user interface for a knowledge-based planning and scheduling systemabstractThe objective of EMPRESS (expert mission planning and replanning scheduling system) is to support the planning and scheduling required to prepare science and application payloads for flight aboard the US Space Shuttle. EMPRESS was designed and implemented in Zetalisp on a 3600 series Symbolics LISP machine. Initially, EMPRESS was built as a concept demonstration system. The system has since been modified and expanded to ensure that the data have integrity. Issues underlying the design and development of the EMPRESS-I interface, results from a system usability assessment, and consequent modifications are described.> Alice M. Mulvehill |
IEEE Trans. Syst. Man Cybern. | 1 |