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Steve Rabin

dblp:51/3871 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

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

Artificial intelligence and machine learning · 3 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 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.

Theoretical computer science
1 paper
Graph algorithms and graph theory · 100%
Artificial intelligence
1 paper
Planning, search and constraint satisfaction · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › pathfinding
grid-based pathfinding
0.212016
Combining Bounding Boxes and JPS to Prune Grid Pathfinding · AAAI 2016
Knowledge, reasoning and agents › Planning, search and constraint satisfaction
pathfinding
0.212016
Combining Bounding Boxes and JPS to Prune Grid Pathfinding · AAAI 2016
Graph algorithms and graph theory › planar graphs
canonical orderings
0.212016
Canonical Orderings on Grids · IJCAI 2016
Graph algorithms and graph theory › graph algorithms
graph search
0.212016
Canonical Orderings on Grids · IJCAI 2016
Graph algorithms and graph theory › planar graphs
grid graphs
0.112016
Canonical Orderings on Grids · IJCAI 2016

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

canonical orderings · 0.2bounding boxes · 0.2JPS+ · 0.2
YearPublicationVenuePosition
2016 Combining Bounding Boxes and JPS to Prune Grid Pathfinding
abstract
Pathfinding is a common task across many domains and platforms, whether in games, robotics, or road maps. Given the breadth of domains, there are also a wide variety of representations used for pathfinding, and there are many techniques which have been shown to improve performance. In the last few years, the state-of-the-art in grid-based pathfinding has been significantly improved with domain-specific techniques such as Jump Point Search (JPS), Subgoal Graphs, and Compressed Path Databases. In this paper we look at a specific implementation of the general idea of Geometric Containers, showing that, while it is effective on grid maps, when combined with JPS+ it provides state-of-the-art performance.
Steve Rabin, Nathan R. Sturtevant
AAAI1
2016 Canonical Orderings on Grids
Nathan R. Sturtevant, Steve Rabin
IJCAI2
2015 The Grid-Based Path Planning Competition: 2014 Entries and Results
abstract
The Grid-Based Path Planning Competition has just completed its third iteration. The entriesused in the competition have improved significantly during this time, changing the view ofthe state of the art of grid-based pathfinding. Furthermore, the entries from the competition have beenmade publicly available, improving the ability of researchers to compare their work. Thispaper summarizes the entries to the 2014 competition, presents the 2014 competition results,and talks about what has been learned and where there is room for improvement.
Nathan R. Sturtevant, Jason M. Traish, James R. Tulip, Tansel Uras, Sven Koenig, Ben Strasser, Adi Botea, Daniel Harabor, Steve Rabin
SOCS9