Exploratory combinatorial optimization with reinforcement learning
Many real-world problems can be reduced to combinatorial optimization on a graph, where the subset or ordering of vertices that maximize some objective function must be found. With such tasks often NP-hard and analytically intractable, reinforcement learning (RL) has shown promise as a framework wit...
| Váldodahkkit: | , , , |
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| Materiálatiipa: | Conference item |
| Giella: | English |
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Association for the Advancement of Artificial Intelligence
2020
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