Presence and absence of pathology on game trees
Advances in computer chess
Experiments on alternatives to minimax
International Journal of Parallel Programming
AI Magazine
Comparison of the minimax and product back-up rules in a variety of games
Search in Artificial Intelligence
Recursive random games: a probabilistic model for perfect information games
Recursive random games: a probabilistic model for perfect information games
The Secret of Selective Game Tree Search, When Using Random-Error Evaluations
STACS '02 Proceedings of the 19th Annual Symposium on Theoretical Aspects of Computer Science
From State-of-the-Art Static Fleet Assignment to Flexible Stochastic Planning of the Future
Algorithmics of Large and Complex Networks
Strategy generation in multi-agent imperfect-information pursuit games
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Parallelism for perturbation management and robust plans
Euro-Par'05 Proceedings of the 11th international Euro-Par conference on Parallel Processing
Player modeling, search algorithms and strategies in multi-player games
ACG'05 Proceedings of the 11th international conference on Advances in Computer Games
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Since there existed no convincing theoretical explanation for the usually observed benefits of minimax search in practice, we investigated two instances of a class of tree models which are based on the concept of quiescence. (This way the strict separation or static and dynamic aspects in prac tical programs is modeled.) We performed Monte Carlo simulations, enhanced by analytic results. The behaviour of these models in our studies gen erally corresponds quite well to observations in practice (especially that of the model based on the more restrictive definition of quiescence). Hence, we found empirical evidence for an earlier conjec ture, and these results can serve as an important step towards understanding the reason for the benefits of minimax search.