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Moerland et al., 2018 - Google Patents

A0c: Alpha zero in continuous action space

Moerland et al., 2018

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Document ID
4825261290556534609
Author
Moerland T
Broekens J
Plaat A
Jonker C
Publication year
Publication venue
arXiv preprint arXiv:1805.09613

External Links

Snippet

A core novelty of Alpha Zero is the interleaving of tree search and deep learning, which has proven very successful in board games like Chess, Shogi and Go. These games have a discrete action space. However, many real-world reinforcement learning domains have …
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