What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Machine learning
His primary areas of investigation include Algorithm, Mathematical optimization, Heuristics, Heuristic and Database.
His work on Heuristic function and Branching factor as part of general Algorithm research is frequently linked to Terrain and Simple, bridging the gap between disciplines.
His work on Search algorithm as part of general Mathematical optimization study is frequently linked to Speedup, bridging the gap between disciplines.
His studies examine the connections between Heuristics and genetics, as well as such issues in Disjoint sets, with regards to Admissible heuristic.
His study focuses on the intersection of Heuristic and fields such as Incremental heuristic search with connections in the field of Problem domain and Reduction.
His Tree research integrates issues from Node, Solver, Task and Pruning.
His most cited work include:
- Theta*: any-angle path planning on grids (266 citations)
- Conflict-based search for optimal multi-agent pathfinding (201 citations)
- Disjoint pattern database heuristics (179 citations)
What are the main themes of his work throughout his whole career to date?
Ariel Felner mostly deals with Mathematical optimization, Heuristics, Path, Algorithm and Heuristic.
In most of his Mathematical optimization studies, his work intersects topics such as Task.
His work deals with themes such as Disjoint sets, Graph and Admissible heuristic, which intersect with Heuristics.
His study on Pathfinding is often connected to Focus, Grid and Set as part of broader study in Path.
His research integrates issues of Node and Database in his study of Algorithm.
His research investigates the connection between Heuristic and topics such as Theoretical computer science that intersect with issues in State.
He most often published in these fields:
- Mathematical optimization (47.96%)
- Heuristics (25.00%)
- Path (23.47%)
What were the highlights of his more recent work (between 2018-2020)?
- Mathematical optimization (47.96%)
- Path (23.47%)
- Heuristics (25.00%)
In recent papers he was focusing on the following fields of study:
Ariel Felner mainly focuses on Mathematical optimization, Path, Heuristics, Graph and Grid.
Ariel Felner combines subjects such as Upper and lower bounds and Probabilistic logic with his study of Mathematical optimization.
He combines subjects such as Disjoint sets and Topology with his study of Path.
Ariel Felner interconnects Point, Solver and Reduction in the investigation of issues within Heuristics.
His research in Graph intersects with topics in Machine learning, Travelling salesman problem and Admissible heuristic.
Ariel Felner works mostly in the field of Task, limiting it down to concerns involving Metric and, occasionally, Algorithm.
Between 2018 and 2020, his most popular works were:
- Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks. (35 citations)
- Multi-Agent Path Finding for Large Agents (28 citations)
- Multi-Agent Pathfinding: Definitions, Variants, and Benchmarks (22 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Topology
His main research concerns Path, Mathematical optimization, Grid, Topology and Disjoint sets.
He integrates Path with Set in his research.
Heuristics is the focus of his Mathematical optimization research.
His Heuristics research includes themes of Point, Solver and Reduction.
His study of Grid brings together topics like Operations research, Job shop scheduling, Key, Benchmark and Pathfinding.
His research on Disjoint sets frequently connects to adjacent areas such as Orders of magnitude.
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