Nathan Sturtevant
Nathan Sturtevant
University of Alberta, Alberta Machine Intelligence Institute (Amii)
Verified email at - Homepage
Cited by
Cited by
Conflict-based search for optimal multi-agent pathfinding
G Sharon, R Stern, A Felner, NR Sturtevant
Artificial Intelligence 219, 40-66, 2015
Benchmarks for grid-based pathfinding
NR Sturtevant
IEEE Transactions on Computational Intelligence and AI in Games 4 (2), 144-148, 2012
Partial pathfinding using map abstraction and refinement
N Sturtevant, M Buro
AAAI 5, 1392-1397, 2005
Multi-agent pathfinding: Definitions, variants, and benchmarks
R Stern, NR Sturtevant, A Felner, S Koenig, H Ma, TT Walker, J Li, ...
Twelfth Annual Symposium on Combinatorial Search, 2019
An analysis of UCT in multi-player games
N Sturtevant
ICGA Journal 31 (4), 195-208, 2008
Search-based optimal solvers for the multi-agent pathfinding problem: Summary and challenges
A Felner, R Stern, SE Shimony, E Boyarski, M Goldenberg, G Sharon, ...
Tenth Annual Symposium on Combinatorial Search, 2017
Enhanced partial expansion A*
M Goldenberg, A Felner, R Stern, G Sharon, N Sturtevant, RC Holte, ...
Journal of Artificial Intelligence Research 50, 141-187, 2014
Graph abstraction in real-time heuristic search
V Bulitko, N Sturtevant, J Lu, T Yau
Journal of Artificial Intelligence Research 30, 51-100, 2007
Understanding the success of perfect information monte carlo sampling in game tree search
JR Long, NR Sturtevant, M Buro, T Furtak
Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010
On pruning techniques for multi-player games
NR Sturtevant, RE Korf
AAAI/IAAI 49, 201-207, 2000
Memory-based heuristics for explicit state spaces
NR Sturtevant, A Felner, M Barrer, J Schaeffer, N Burch
Twenty-First International Joint Conference on Artificial Intelligence, 2009
Memory-Efficient Abstractions for Pathfinding.
NR Sturtevant
AIIDE 684, 31-36, 2007
Improving state evaluation, inference, and search in trick-based card games
M Buro, JR Long, T Furtak, N Sturtevant
Twenty-First International Joint Conference on Artificial Intelligence, 2009
Improving Collaborative Pathfinding Using Map Abstraction.
NR Sturtevant, M Buro
AIIDE, 80-85, 2006
A polynomial-time algorithm for non-optimal multi-agent pathfinding
MM Khorshid, RC Holte, NR Sturtevant
Fourth Annual Symposium on Combinatorial Search, 2011
Partial-expansion A* with selective node generation
A Felner, M Goldenberg, G Sharon, R Stern, T Beja, N Sturtevant, ...
Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012
TBA*: time-bounded A
Y Björnsson, V Bulitko, N Sturtevant
Twenty-first international joint conference on artificial intelligence, 2009
Feature construction for reinforcement learning in hearts
NR Sturtevant, AM White
International Conference on Computers and Games, 122-134, 2006
Inconsistent heuristics in theory and practice
A Felner, U Zahavi, R Holte, J Schaeffer, N Sturtevant, Z Zhang
Artificial Intelligence 175 (9-10), 1570-1603, 2011
Simultaneously searching with multiple settings: An alternative to parameter tuning for suboptimal single-agent search algorithms
RA Valenzano, N Sturtevant, J Schaeffer, K Buro, A Kishimoto
Twentieth International Conference on Automated Planning and Scheduling, 2010
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