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Experiments on Combinatorial Optimization with Reinforcement Learning Using Deep Learning and Monte Carlo Tree Search and a Consideration of Frame Problem
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- HIKIDA Satoshi
- AGICRON Research Institute, Ltd.
Bibliographic Information
- Other Title
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- 深層学習とモンテカルロ木探索を用いた強化学習の組合せ最適化問題での実験とフレーム問題に関する1考察
Description
<p>Reinforcement learning using deep learning and Monte Carlo tree search has been reported to be extremely effective as an artificial intelligence algorithm that is used in AlphaZero etc. and is widely applicable to various games. Since this method is essentially an algorithm that solves the search problem efficiently, it is possible to solve a general combination optimization problem as well as a game. Therefore, in order to deepen the understanding of this method, experiments were applied to combinatorial optimization problem, and the results are reported. The relationship between this method and the frame problem also be described.</p>
Journal
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- JSAI Technical Report, Type 2 SIG
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JSAI Technical Report, Type 2 SIG 2018 (AGI-009), 07-, 2018-08-30
The Japanese Society for Artificial Intelligence
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Details 詳細情報について
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- CRID
- 1390007923750359808
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- NII Article ID
- 130008089090
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- ISSN
- 24365556
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Allowed