Demo Data from EDBT 2026 / reviewers in the wild / expert
John Loch
dblp:29/5370
· DBLP profile ↗
4ranked-venue papers
2as first author
0since 2021 · last 1998
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 2 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1Applied, interdisciplinary, general and emerging computing · 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
4 papers |
Planning, search and constraint satisfaction · 32% Motion planning and robot control · 19% Robot navigation and mapping · 18% |
Topics — the 10 heaviest of 10, 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
partially observable markov decision process |
0.0 | 2 | 1998 | The Effect of Eligibility Traces on Finding Optimal Memoryless Policies in Partially Observable Markov Decision Processes · NIPS 1998 Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes · ICML 1998 |
Machine learning › Reinforcement learning › temporal difference learning
eligibility traces |
0.0 | 1 | 1998 | The Effect of Eligibility Traces on Finding Optimal Memoryless Policies in Partially Observable Markov Decision Processes · NIPS 1998 |
Robotics › Motion planning and robot control › robot control
behavior-based control |
0.0 | 1 | 1994 | Behavior control for robotic exploration of planetary surfaces · IEEE Trans. Robotics Autom. 1994 |
Robotics › Robot navigation and mapping
mobile robot navigation |
0.0 | 1 | 1994 | Behavior control for robotic exploration of planetary surfaces · IEEE Trans. Robotics Autom. 1994 |
Robotics › Legged, aerial and field robots › field robotics
planetary rover |
0.0 | 1 | 1994 | Behavior control for robotic exploration of planetary surfaces · IEEE Trans. Robotics Autom. 1994 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1994 | Behavior control for robotic exploration of planetary surfaces · IEEE Trans. Robotics Autom. 1994 |
Robotics › Robot navigation and mapping › mobile robot navigation
reactive navigation |
0.0 | 1 | 1992 | Reactive Navigation through Rough Terrain: Experimental Results · AAAI 1992 |
Robotics › Robot manipulation
autonomous manipulation |
0.0 | 1 | 1994 | Behavior control for robotic exploration of planetary surfaces · IEEE Trans. Robotics Autom. 1994 |
Robotics › Legged, aerial and field robots
field robotics |
0.0 | 1 | 1992 | Reactive Navigation through Rough Terrain: Experimental Results · AAAI 1992 |
Robotics › Robot navigation and mapping › mobile robot navigation › terrain-aware navigation
rough terrain navigation |
0.0 | 1 | 1992 | Reactive Navigation through Rough Terrain: Experimental Results · AAAI 1992 |
Methods — techniques the papers use, named apart from their topics
eligibility traces · 0.0behavior control architecture · 0.0reactive control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1998 | Using Eligibility Traces to Find the Best Memoryless Policy in Partially Observable Markov Decision Processes
John Loch, Satinder Singh 0001 |
ICML | 1 |
| 1998 | The Effect of Eligibility Traces on Finding Optimal Memoryless Policies in Partially Observable Markov Decision Processes
John Loch |
NIPS | 1 |
| 1994 | Behavior control for robotic exploration of planetary surfacesabstractThis paper describes a series of robots developed at JPL to demonstrate the feasibility of using a behavior-control approach to control small robots on planetary surfaces. The round-trip light-time delay makes direct teleoperation of a mobile robot on a planetary surface impossible. Planetary rovers must therefore possess a certain degree of autonomy. However, small robots can only support small computers (due mostly to power, not size constraints). Behavior control provides a means of autonomous control that requires very little computation. The robots described in this paper all used 8-bit, 1-MIP microprocessors with as little as 4 k and no more than 40 k of memory, and extremely simple sensors. Despite these limitations they reliably perform both autonomous navigation and manipulation in both indoor and outdoor rough-terrain environments.> Erann Gat, Rajiv S. Desai, Robert Ivlev, John Loch, David P. Miller |
IEEE Trans. Robotics Autom. | 4 |
| 1992 | Reactive Navigation through Rough Terrain: Experimental Results
David P. Miller, Rajiv S. Desai, Erann Gat, Robert Ivlev, John Loch |
AAAI | 5 |