Artificial Intelligence in Strategic Computer Games

Tato prce se zabv metodami pou­vanmi v umÄl© inteligenci strategickch poÄ­taÄovch her, mnoh© z tÄchto metod jsou vak pouiteln© i v jinch oblastech. Jsou to rzn© metody pro rozhodovn­ (nap. stavov© automaty, fuzzy logika, markovy etÄzce), plnovn­ (c­lem orientovan© plnovn­, plnovn­ monte-carlo, plnovn­ zaloen© na p­padech) a strojov©ho uÄen­ (posilov© uÄen­, rozhodovac­ stromy a neuronov© s­tÄ). C­lem t©to prce je tyto metody z rznch zdroj nastudovat a vysvÄtlit zkladn­ princip nÄkolika z nich. Pot© nÄkolik vybranch metod rozebrat v­ce do dopodrobna a implementovat je (c­lem orientovan© plnovn­ a stavov automat). Pi implementaci a nsledn©m testovn­ byl vyuit hern­ engine ORTS, kterm se tato prce tak© zabv.This work covers with artificial intelligence of strategy computer games, however many of these methods are usable in other areas. These are different methods used in deciding (finite state machina, fuzzy logic, Markov Process), planning (Goal-oriented action planning, Montecarlo planning, Case-based planning) and machine learning ( Reinforcement leasing, Decision Learning and Neural Networks). Objective of this thesis is to study this methods from different sources and explain their base principle. Then few of this methods resolve in more details and implement them (goal oriented planning and state machine). This thesis focuses on game engine ORTS, which is used in implementing and testing methods.