PARALLEL MONTE CARLO METHOD IN GRID WORLD (REINFORCEMENT LEARNING) USING CUDA DYNAMIC PARALLELISM
Parallel Monte Carlo method for reinforcement learning problem has been shown to be able to accelerate agents’ experience quality gain per episode by increasing number of agents. Previous researches have experimented on this with up to 16 parallel agents. The rapid development of GPGPU, especiall...
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| Format: | Theses |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/39712 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
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