Parallelization of evolution of reinforcement learning agents using GPGPU
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- SENGA Yoshiki
- Nagoya Institute of Technology
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- MORIYAMA Kouichi
- Nagoya Institute of Technology
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- MUTOH Atsuko
- Nagoya Institute of Technology
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- MATSUI Tohgoroh
- Chubu University
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- NOBUHIRO Inuzuka
- Nagoya Institute of Technology
Bibliographic Information
- Other Title
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- GPGPUを用いた強化学習エージェントの並列進化シミュレーション
Abstract
<p>GPGPU is a parallel computation technology using GPU that has huge number of processor cores for parallelly calculating colors of pixels on a monitor. In a previous work, we used GPGPU to parallelize many runs of reinforcement learning agents for calculating their tness in a simulation of evolution. It speeded up the simulation surprisingly. However, the evolution part was sequentially run in CPU and the communication between CPU and GPU happened in every generation. Hence, this work uses GPGPU to parallelize the evolution part in addition to the tness calculation. It makes the simulation even faster due to parallelism and the reduction of latency between CPU and GPU.</p>
Journal
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2018 (0), 2P103-2P103, 2018
The Japanese Society for Artificial Intelligence
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Details 詳細情報について
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- CRID
- 1390001288048198144
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- NII Article ID
- 130007423832
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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
- Disallowed