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- W4232596103 abstract "The domain of Artificial Intelligence (AI) Search algorithms is a well-studied area. A variety of AI search algorithms have been developed in the past decades. Some of them are considered to be among the main AI search algorithms such as Best First Search, A*, Iterative Deepening Search, etc. The others use these main algorithms as a basis and include more heuristics to generate newer algorithms such as Iterative Deepening A* (IDA*), Branch and Bound Search, etc. the innovation of this research is a new approach to the AI search algorithms, we called it indexed search. The methods assigns integer indices to the states of the problem and instead of searching for the goal state, it searches for the index of the goal state. Once the index of a goal state found, we convert that index from decimal base to the base of the branching factor of the problem, and this new number is the solution path from goal to the start node. The new approach eliminates the Closed List which employed for most AI search algorithms to store the explored nodes. The new approach also generates a solution path faster than the respective versions of them and it also use less memory space." @default.
- W4232596103 created "2022-05-12" @default.
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- W4232596103 date "2019-01-01" @default.
- W4232596103 modified "2023-10-16" @default.
- W4232596103 title "Indexed Search" @default.
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- W4232596103 doi "https://doi.org/10.1007/978-3-030-23367-9_7" @default.
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