Demo Data from EDBT 2026 / reviewers in the wild / expert
Natasha Danas
dblp:204/3764
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 first-authorArtificial intelligence and machine learning · 1Graphics, computer vision, multimedia, augmented reality and games · 1
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
1 paper |
Reinforcement learning · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Requirements engineering and software design · 56% Operating systems · 44% |
Topics — the 5 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Machine learning › Reinforcement learning › markov decision process
factored markov decision process |
0.4 | 1 | 2020 | Task Scoping for Efficient Planning in Open Worlds (Student Abstract) · AAAI 2020 |
Machine learning › Reinforcement learning › function approximation › representation learning for reinforcement learning
state abstraction |
0.4 | 1 | 2020 | Task Scoping for Efficient Planning in Open Worlds (Student Abstract) · AAAI 2020 |
Operating systems
provenance |
0.3 | 1 | 2017 | The power of "why" and "why not": enriching scenario exploration with provenance · ESEC/SIGSOFT FSE 2017 |
Requirements engineering and software design
software architecture |
0.3 | 1 | 2017 | The power of "why" and "why not": enriching scenario exploration with provenance · ESEC/SIGSOFT FSE 2017 |
Requirements engineering and software design
formal specification |
0.1 | 1 | 2017 | The power of "why" and "why not": enriching scenario exploration with provenance · ESEC/SIGSOFT FSE 2017 |
Methods — techniques the papers use, named apart from their topics
state and action variable pruning · 0.4optimal value function · 0.4scenario finding · 0.3provenance · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Task Scoping for Efficient Planning in Open Worlds (Student Abstract)abstractWe propose an abstraction method for open-world environments expressed as Factored Markov Decision Processes (FMDPs) with very large state and action spaces. Our method prunes state and action variables that are irrelevant to the optimal value function on the state subspace the agent would visit when following any optimal policy from the initial state. This method thus enables tractable fast planning within large open-world FMDPs. Nishanth Kumar, Michael Fishman 0001, Natasha Danas, Stefanie Tellex, Michael L. Littman, George Dimitri Konidaris |
AAAI | 3 |
| 2017 | User Studies of Principled Model Finder Output
Natasha Danas, Tim Nelson, Lane Harrison, Shriram Krishnamurthi, Daniel J. Dougherty |
SEFM | 1 |
| 2017 | The power of "why" and "why not": enriching scenario exploration with provenanceabstractScenario-finding tools like the Alloy Analyzer are widely used in numerous concrete domains like security, network analysis, UML analysis, and so on. They can help to verify properties and, more generally, aid in exploring a system's behavior. Tim Nelson, Natasha Danas, Daniel J. Dougherty, Shriram Krishnamurthi |
ESEC/SIGSOFT FSE | 2 |