Skatinamojo mokymosi algoritmų skirtų Sokoban žaidimo agento valdymui palyginimas ; Comparison of reinforcement learning algorithms for sokoban game agent training
Skatinamojo mokymosi algoritmų skirtų Sokoban žaidimo agento valdymui palyginimas ; Comparison of reinforcement learning algorithms for sokoban game agent training
- Neue Suche nach: Rusakevičius, Jokūbas
- Neue Suche nach: Rusakevičius, Jokūbas
- Neue Suche nach: Marcinkevičius, Virginijus
In this thesis, the application of the reinforcement learning agent to the Sokoban game was investigated. The paper describes the theory, basic principles and application techniques of reinforcement learning. Also, different neural networks are described, due to their use in the architecture of reinforcement learning strategies. Thesis reviews Sokoban game environments and state-of-art reinforcement learning libraries, frameworks. The paper compares implementations of different reinforcement learning algorithms and different strategies in the Sokoban game environment. The obtained results of transfer learning are compared to those of an agent trained in an environment of equal complexity without transfer learning. Analysis of the results showed that using transfer learning for the Sokoban game environment, reinforcement learning algorithms can achieve better results.
Dokumentinformationen
Skatinamojo mokymosi algoritmų skirtų Sokoban žaidimo agento valdymui palyginimas ; Comparison of reinforcement learning algorithms for sokoban game agent training
2020-06-10
Hochschulschrift
Elektronische Ressource
Lithuanian , Englisch
| DDC: | 629 |
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