Handling non-stationary data streams under complex environments
In the digital era, where data generation is incessant and often presents non-stationary distributions, intelligent agents face the imperative challenge of emulating human-like learning and adaptation. Handling non-stationary data streams effectively is essential for intelligent agents, enabling th...
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| Format: | Thesis-Doctor of Philosophy |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/178601 |