Demo Data from SIGIR 2026 / reviewers in the wild / expert
Jak Kirman
dblp:39/2764
· DBLP profile ↗
4ranked-venue papers
1as first author
0since 2021 · last 1995
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 4 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-authorGraphics, 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
3 papers |
Planning, search and constraint satisfaction · 80% Motion planning and robot control · 20% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
planning under uncertainty |
0.0 | 2 | 1995 | Planning With Deadlines in Stochastic Domains · AAAI 1993 Planning under Time Constraints in Stochastic Domains · Artif. Intell. 1995 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning under uncertainty
probabilistic planning |
0.0 | 1 | 1995 | Planning under Time Constraints in Stochastic Domains · Artif. Intell. 1995 |
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › temporal planning
time-constrained planning |
0.0 | 1 | 1995 | Planning under Time Constraints in Stochastic Domains · Artif. Intell. 1995 |
Robotics › Motion planning and robot control › mobile robot control
navigation control |
0.0 | 1 | 1991 | Sensor abstractions for control of navigation · ICRA 1991 |
Robotics › Motion planning and robot control › motion planning
sensor-based motion planning |
0.0 | 1 | 1991 | Sensor abstractions for control of navigation · ICRA 1991 |
Methods — techniques the papers use, named apart from their topics
spatial abstraction · 0.0bayesian decision theory · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1995 | Planning under Time Constraints in Stochastic Domains
Thomas L. Dean, Leslie Pack Kaelbling, Jak Kirman, Ann E. Nicholson |
Artif. Intell. | 3 |
| 1993 | Planning With Deadlines in Stochastic Domains
Thomas L. Dean, Leslie Pack Kaelbling, Jak Kirman, Ann E. Nicholson |
AAAI | 3 |
| 1993 | Deliberation Scheduling for Time-Critical Sequential Decision Making
Thomas L. Dean, Leslie Pack Kaelbling, Jak Kirman, Ann E. Nicholson |
UAI | 3 |
| 1991 | Sensor abstractions for control of navigationabstractAn approach to building high-level control systems for robotics that is based on Bayesian decision theory is presented. The authors show how this approach provides a natural and modular way of integrating sensing and planning. They develop a simple solution for a particular problem as an illustration. They also examine the cost of using such a model and consider the areas in which abstraction can reduce this cost. The authors focus on the area of spatial abstraction. They discuss an abstraction that has been used to solve problems involving robot navigation and give a detailed account of the mapping from raw sensor data to the abstraction.> Jak Kirman, Kenneth Basye, Thomas L. Dean |
ICRA | 1 |