Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
All the right moves
Parallel depth first search. Part I. implementation
International Journal of Parallel Programming
Parallel depth first search. Part II. analysis
International Journal of Parallel Programming
Heuristic search in restricted memory (research note)
Artificial Intelligence
Parallel heuristic search: two approaches
Parallel algorithms for machine intelligence and vision
Parallel algorithms for machine intelligence and vision
The design and analysis of algorithms for asynchronous multiprocessors.
The design and analysis of algorithms for asynchronous multiprocessors.
Large-scale parallelization of alpha-beta search: an algorithmic and architectural study with computer chess
A bibliography on minimax trees
ACM SIGACT News
Automating the strategy selection for parallel heuristic search
ACM-SE 36 Proceedings of the 36th annual Southeast regional conference
Transposition table driven work scheduling in distributed search
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
A Performance Analysis of Transposition-Table-Driven Work Scheduling in Distributed Search
IEEE Transactions on Parallel and Distributed Systems
Enhanced Iterative-Deepening Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Annals of Mathematics and Artificial Intelligence
The Journal of Supercomputing
Performance evaluation of parallel iterative deepening A* on clusters of workstations
Performance Evaluation - Performance modelling and evaluation of high-performance parallel and distributed systems
Adaptive parallel iterative deepening search
Journal of Artificial Intelligence Research
Complete solution of the eight-puzzle and the benefit of node ordering in IDA
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Are many reactive agents better than a few deliberative ones?
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Experimenting with IDA* search algorithm in heterogeneous pervasive environments
Artificial Intelligence Review
Maximizing the benefits of parallel search using machine learning
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Best-first heuristic search for multicore machines
Journal of Artificial Intelligence Research
Solving the traveling tournament problem with iterative-deepening A*
Journal of Scheduling
Evaluation of a simple, scalable, parallel best-first search strategy
Artificial Intelligence
Hi-index | 0.14 |
Parallel window search is applied to single-agent problems by having different processes simultaneously perform iteration of Iterative-Deepening-A* (IDA*) on the same problem but with different cost thresholds. This approach is limited by the time to perform the goal iteration. To overcome this disadvantage, the authors consider node ordering. They discuss how global node ordering by minimum h among nodes with equal f=g+h values can reduce the time complexity of serial IDA* by reducing the time to perform the iterations prior to the goal iteration. Finally, the two ideas of parallel window search and node ordering are combined to eliminate the weaknesses of each approach while retaining the strengths. The resulting approach, called simply parallel window search, can be used to find a near-optimal solution quickly, improve the solution until it is optimal, and then finally guarantee optimality, depending on the amount of time available.