Creation and implementation of a set of game strategies based on training neural networks with reinforcement learning
| Autor: | D S Kozlov, O N Polovikova |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 2134:012005 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/2134/1/012005 |
| Popis: | The study explores the problems of reinforcement learning and finding non-obvious play strategies using reinforcement learning. Two approaches to agent training (blind and pattern-based) are considered and implemented. The advantage of the self-learning approach with reinforcement using patterns as applied to a specific game (tic-tac-toe five in a row) is shown. Recorded and analyzed the use of unusual strategies by an agent using a pattern-based approach. |
| Databáze: | OpenAIRE |
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