Genetic algorithm has been widely used in different areas of optimization problems. Ithas been combined with renewable energy domain, photovoltaic system, in this thesis.To participate and win the solar boat race, a control program is needed and C++ hasbeen chosen for programming. To implement the program, the mathematic model hasbeen built. Besides, the approaches to calculate the boundaries related to conditionhave been explained. Afterward, the processing of the prediction and real time controlfunction are offered. The program has been simulated and the results proved thatgenetic algorithm is helpful to get the good results but it does not improve the resultstoo much since the particularity of the solar driven boat project such as the limitationof energy production

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.

This report explores if Monte-Carlo Tree Search (MCTS) can perform well in Fox Game, a classic Scandinavian strategy game. MCTS is implemented using a cutoff in the simulation phase. The game state is then evaluated using a heuristic function that is formulated using theoretical arguments from its chess counterpart. MCTS is shown to perform on the same level as highly experienced human players using limited computational resources. The method is used to explore how the imbalance in Fox Game (favoring sheep) can be mended by reducing the number of sheep pieces from 20 to 18. / I denna rapport undersöks om Monte-Carlo trädsökning (MCTS) kan prestera väl i rävspel, ett klassiskt skandinaviskt strategispel. MCTS implementeras med en cutoff i simuleringsfasen. Speltillståndet utvärderas där med hjälp av en heuristisk funktion som formuleras med hjälp av teoretiska argument från dess motsvarighet i schack. MCTS med endast begränsade beräkningsresurser visas kunna prestera på samma nivå som mycket erfarna människor. Metoden används för att utforska hur obalansen i rävspel (som gynnar får) kan förbättras genom att minska antalet fårpjäser från 20 till 18. / Kandidatexjobb i elektroteknik 2022, KTH, Stockholm