| Language: | Slovenian |
|---|---|
| Year of publishing: | 2022 |
| Typology: | 2.11 - Undergraduate Thesis |
| Organization: | UM FERI - Faculty of Electrical Engineering and Computer Science |
| Publisher: | [M. Polner] |
| UDC: | 004.8:004.94(043.2) |
| COBISS: |
139102979
|
| Views: | 136 |
| Downloads: | 22 |
| Average score: | 0 (0 votes) |
| Metadata: |
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| Secondary language: | English |
|---|---|
| Secondary title: | Teaching a neural network to play a simple arcade game |
| Secondary abstract: | The thesis aimed to create a neural network and a simple arcade video game called Bomberman that the neural network would learn to play. The video game was created using the open-source framework LibGdx in the Java programming language. We implemented our own neural network and a neural network based on the PyTorch library. Both networks learn using the reinforcement learning method. The results of our own implementation of the neural network were compared with the results of the neural network implemented with the PyTorch library. We found that the results of both networks are very similar. After thirty minutes of learning, the neural network manages to clear half of all destructible walls. |
| Secondary keywords: | arcade video game;Bomberman;neural network;reinforcement learning;deep Q-network; |
| Type (COBISS): | Bachelor thesis/paper |
| Thesis comment: | Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije |
| Pages: | 1 spletni vir (1 datoteka PDF (X, 48 f.)) |
| ID: | 16374780 |