Exploration and value function factorisation in single and multi-agent reinforcement learning
<p>The ability to learn from data is crucial in developing satisfactory solutions to many complex problems. In particular, in the design of intelligent agents that exist and interact with a complex environment in the pursuit of some goal. In this thesis we investigate some bottlenecks that can...
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| Muut tekijät: | |
| Aineistotyyppi: | Opinnäyte |
| Kieli: | English |
| Julkaistu: |
2021
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