His primary areas of study are Model checking, Theoretical computer science, Heuristic, Beam search and Incremental heuristic search. Model checking is a primary field of his research addressed under Algorithm. His study in Algorithm is interdisciplinary in nature, drawing from both Multiprocessing and Partially ordered set.
His Theoretical computer science research includes themes of Representation and State. His research on Heuristic concerns the broader Mathematical optimization. His Incremental heuristic search research incorporates themes from Heuristics and Database.
His scientific interests lie mostly in Theoretical computer science, Model checking, Algorithm, Beam search and Artificial intelligence. His Theoretical computer science research incorporates elements of State space search, Graph, Set and State. His Model checking research is multidisciplinary, incorporating elements of Liveness and Asynchronous communication.
His research in Algorithm is mostly concerned with Search algorithm. His Beam search study results in a more complete grasp of Mathematical optimization. His study looks at the intersection of Incremental heuristic search and topics like Heuristic with Benchmark and Graph.
The scientist’s investigation covers issues in Travelling salesman problem, Artificial intelligence, Set, Tree and Model checking. In general Artificial intelligence, his work in Automated planning and scheduling and Motion planning is often linked to Trajectory and Game playing linking many areas of study. His Tree study integrates concerns from other disciplines, such as Adaptation and Benchmark.
He has included themes like Rotation formalisms in three dimensions, Management science and Asynchronous communication in his Model checking study. Stefan Edelkamp integrates many fields, such as Multiple sequence alignment and engineering, in his works. His work is dedicated to discovering how Theoretical computer science, Heuristics are connected with Search algorithm and other disciplines.
Stefan Edelkamp mostly deals with Tree, Travelling salesman problem, Beam search, Artificial intelligence and Theoretical computer science. While the research belongs to areas of Tree, Stefan Edelkamp spends his time largely on the problem of Motion planning, intersecting his research to questions surrounding Motion and Set. Stefan Edelkamp studies Beam search, namely Combinatorial search.
His work on Automated planning and scheduling and Heuristic as part of general Artificial intelligence research is frequently linked to Competition, bridging the gap between disciplines. His Theoretical computer science research is multidisciplinary, relying on both Best-first search, Similarity, Overhead and Benchmark. His biological study spans a wide range of topics, including Symbolic-numeric computation and Heuristics.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Planning with Pattern Databases
Sixth European Conference on Planning (2014)
Heuristic Search: Theory and Applications
Stefan Edelkamp;Stefan Schroedl;Sven Koenig.
Directed explicit model checking with HSF-SPIN
Stefan Edelkamp;Alberto Lluch Lafuente;Stefan Leue.
international workshop on model checking software (2001)
Route planning and map inference with global positioning traces
Stefan Edelkamp;Stefan Schrödl.
Lecture Notes in Computer Science (2003)
Directed explicit-state model checking in the validation of communication protocols
Stefan Edelkamp;Stefan Leue;Alberto Lluch-Lafuente.
International Journal on Software Tools for Technology Transfer (2004)
Time complexity of iterative-deepening-A
Richard E. Korf;Michael Reid;Stefan Edelkamp.
Artificial Intelligence (2001)
The deterministic part of IPC-4: an overview
Jörg Hoffmann;Stefan Edelkamp.
Journal of Artificial Intelligence Research (2005)
Incremental map generation with GPS traces
R. Bruntrup;S. Edelkamp;S. Jabbar;B. Scholz.
ieee intelligent transportation systems (2005)
MIPS: The Model-Checking Integrated Planning System
Stefan Edelkamp;Malte Helmert.
Ai Magazine (2001)
Exhibiting Knowledge in Planning Problems to Minimize State Encoding Length
Stefan Edelkamp;Malte Helmert.
Lecture Notes in Computer Science (1999)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: