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Informed searching in state space using A* algorithm
Kobr, Dan ; Berka, Petr (advisor) ; Ivánek, Jiří (referee)
This master's thesis deals with informed search algorithms. It's theoretical section summarizes basic theoretical ideas and terms which are related to this topic. It means especially discrete mathematics, graph theory, artificial intelligence and agent systems. Cardinal aim of this section is to provide theoretical analysis of search algorithms and to classify them into informed and uninformed classes. Theoretical section describes basic search strategies such as breadth first search, deep first search and modifications of these strategies, then it is focused on informed search algorithms, specifically A* (A-Star), IDA* (Iterative Deepening A-Star) and SMA* (Simplified Memory bounded A-star). It also describes topics related to informed search strategies -- heuristic functions and problem relaxation method. Given algorithms are analyzed in order to compare their time and space complexity. Main goal of practical part of this thesis is to design and implement software application, which will use informed and uninformed search strategies described in theoretical section. This application is intended to solve fifteen puzzle problem, so-called Lloyds fifteen puzzle game. First part of practical section analyses fifteen puzzle from mathematical and informatical perspective, then it examines possible implementation variants of algorithms and heuristics and proposes design of the application. Description of main interfaces and classes of the realized application follows. At the end of this section the analysis of informed algorithms and heuristics is performed using the implemented application and obtained results are compared to theoretical characteristics of these algorithms.
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