Search results for "Alpha–beta pruning"
showing 2 items of 2 documents
Fuzzified Game Tree Search – Precision vs Speed
2012
Most game tree search algorithms consider finding the optimal move. That is, given an evaluation function they guarantee that selected move will be the best according to it. However, in practice most evaluation functions are themselves approximations and cannot be considered "optimal". Besides, we might be satisfied with nearly optimal solution if it gives us a considerable performance improvement. In this paper we present the approximation based implementations of the fuzzified game tree search algorithm. The paradigm of the algorithm allows us to efficiently find nearly optimal solutions so we can choose the "target quality" of the search with arbitrary precision --- either it is 100% (pr…
Fuzzified Tree Search in Real Domain Games
2011
Fuzzified game tree search algorithm is based on the idea that the exact game tree evaluation is not required to find the best move. Therefore, pruning techniques may be applied earlier resulting in faster search and greater performance. Applied to an abstract domain, it outperforms the existing ones such as Alpha-Beta, PVS, Negascout, NegaC*, SSS*/ Dual* and MTD(f). In this paper we present experimental results in real domain games, where the proposed algorithm demonstrated 10 percent performance increase over the existing algorithms.