Mitja Lustrek and Vadim Bulitko
Thinking
Too Much: Pathology in Pathfinding
The 18th European Conference on Artificial Intelligence (ECAI)
Patras, Greece, 2008
Alejandro Isaza, Csaba Szepesvári, Vadim Bulitko and Russell
Greiner
Speeding
Up Planning in Markov Decision Processes via Automatically Constructed
Abstractions
The 24th Conference on Uncertainty in Artificial Intelligence (UAI)
Helsinki, Finland, 2008
Vadim Bulitko, Mitja Lušrek, Jonathan Schaeffer, Yngvi Björnsson and
Sverrir Sigmundarson
Dynamic
Control in Real-Time Heuristic Search
Journal of Artificial Intelligence Research (JAIR), Vol 32, 419-452,
2008
Alejandro Isaza, Jieshan Lu, Vadim Bulitko and Russell Greiner
A
Cover-Based Approach to Multi-Agent Moving Target Pursuit
The Fourth Conference on Artificial Intelligence and Interactive Digital
Entertainment (AIIDE)
Stanford, California, 2008
Vadim Bulitko, Nathan Sturtevant, Jieshan Lu and Timothy Yau
Graph
Abstraction in Real-time Heuristic Search
Journal of Artificial Intelligence Research (JAIR), Vol 30, 51-100,
2007
D. Chris Rayner, Katherine Davison, Vadim Bulitko, Kenneth Anderson and
Jieshan Lu
Real-Time
Heuristic Search with a Priority Queue
Proceedings of the International Joint Conference on Artificial
Intelligence (IJCAI), 2372-2377
Hyderabad, India, 2007
Alborz Geramifard, Pirooz Chubak and Vadim Bulitko
Biased
Cost Pathfinding
Proceedings of the Artificial Intelligence and Interactive Digital
Entertainment conference (AIIDE), 112-114
Marina del Rey, California, 2006
Vadim Bulitko and Greg Lee
Learning
in Real Time Search: A Unifying Framework
Journal of Artificial Intelligence Research (JAIR), Vol 25, 119-157,
2006
Vadim Bulitko and Mitja Luvstrek
Lookahead
Pathology in Real-Time Path-Finding
Proceedings of the National Conference on Artificial Intelligence
(AAAI), AAAI Member Abstracts and Posters
Boston, Massachusetts, 2006
Nathan Sturtevant and Michael Buro
Improving Collaborative Pathfinding Using Map Abstraction
AIIDE, Marina del Rey, CA, 2006.
Douglas Demyen and Michael Buro
Efficient Triangulation-Based Pathfinding
AAAI, Boston 2006
Nathan Sturtevant and Michael Buro
Partial Pathfinding Using Map Abstraction and Refinement
AAAI, Pittsburgh, 2005.
Y. Björnsson, M. Enzenberger, R. Holte,
and J. Schaeffer.
Fringe Search: Beating A
IEEE Symposium on Computational Intelligence and Games, Essex, 2005.
A. Botea, M. Müller, and J. Schaeffer
Near Optimal Hierarchical Path-finding.
In Journal of Game Development, volume 1, issue 1, 2004.
Y. Björnsson, M. Enzenberger, R. Holte, J. Schaeffer,
and P. Yap.
Comparison of Different Abstractions for Pathfinding on Maps.
International Joint Conference on Artificial Intelligence (IJCAI'03), 2003.
P. Yap.
Grid-based Pathfinding.
In proceedings of 15th Canadian Conference on Artificial Intelligence,
Calgary, 2002.
P. Yap.
New Ideas in Pathfinding.
In proceedings of AAAI Spring Symposium: Artificial Intelligence and
Interactive Entertainment, pp 95-97, Stanford, 2002.
P. Yap and J. Schaeffer.
Path-finding on a Grid.
In proceedings of 5th Joint Conference of Information Sciences (JCIS 2002),
pp 454-457, Durham, 2002.
The pathfinding library is a testbed for running experiments with pathfinding algorithms with emphasis on environments found in computer games.
| Version | Date | File | Documentation |
|---|---|---|---|
| 0.1.0 | 2003-08-07 | Download | View |
HPA* is a software package for hierarchical path-finding.
The model behind HPA* is described and evaluated in the paper
"Near Optimal Hierarchical Path-Finding" listed above.
Download HPA*