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1.
A framework for multi-objective optimization of virtual tree pruning based on growth simulation
Damjan Strnad, Štefan Kohek, Bedrich Benes, Simon Kolmanič, Borut Žalik, 2020, izvirni znanstveni članek

Opis: We present a framework for multi-objective optimization of fruit tree pruning within a simulated environment, where pruning is performed on a virtual tree model, and its effects on tree growth are observed. The proposed framework uses quantitative measures to express the short-term and long-term effects of pruning, for which potentially conflicting optimization objectives can be defined. The short-term objectives are evaluated on the pruned tree model directly, while the values of long-term objectives are estimated by executing a tree growth simulation. We demonstrate the concept by using a bi-objective case, where the estimated light interceptions of the pruned tree in the current and the next season are used to define separate optimization objectives. We compare the performance of the multi-objective simulated annealing and the NSGA-II method in building the sets of non-dominated pruning solutions. The obtained Pareto front approximations correspond to diverse pruning solutions that balance between optimizing either objective to different extents, which indicates a potential for new applications of the multi-objective pruning optimization concept.
Ključne besede: virtual tree pruning, multi-objective oiptimization, growth simulation, simulated annealing, NSGA-II
Objavljeno v DKUM: 10.07.2023; Ogledov: 390; Prenosov: 62
.pdf Celotno besedilo (1,60 MB)
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2.
Visualization of alpha-beta game tree search : magistrsko delo
Emilija Taseva, 2019, diplomsko delo

Opis: Algorithms make up a crucial part of computer science studies. Learning and understanding new algorithms can be quite interesting, but also hard and complex, especially for students. Visualization can significantly help with the understanding of the dynamic behaviour of algorithms by visually displaying each step of the algorithm, its purpose and how it changes the data. Besides faster and more efficient learning, the better understanding can also lead to potential algorithm improvements in the future. The goal of this thesis is visualization of the alpha-beta tree search algorithm for determining the next optimal move in a two-player, zero-sum, complete information game. The algorithm is visualized using two games, Tic-Tac-Toe and Othello. The algorithm operation can also be demonstrated using a custom tree with parameters chosen by the user.
Ključne besede: algorithm visualization, minimax algorithm, alpha-beta pruning, adversarial search
Objavljeno v DKUM: 08.11.2019; Ogledov: 1262; Prenosov: 79
.pdf Celotno besedilo (1,52 MB)

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