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Trax solver on Zynq with Deep Q-Network | IEEE Conference Publication | IEEE Xplore

Trax solver on Zynq with Deep Q-Network


Abstract:

A software/hardware co-design system for a Trax solver is proposed. Implementation of Trax AI is challenging due to its complicated rules, so we adopted an embedded syste...Show More

Abstract:

A software/hardware co-design system for a Trax solver is proposed. Implementation of Trax AI is challenging due to its complicated rules, so we adopted an embedded system called Zynq (Zynq-7000 AP SoC) and introduced a High Level Synthesis (HLS) design. We also added Deep Q-Network, a machine learning algorithm, to the system for use as an evaluation function. Our solver automatically optimizes its own evaluation function through games with humans or other AIs. The implemented solver works with a 150-MHz clock on the Xilinx XC7Z020-CLG484 of a Digilent ZedBoard. A part of the Deep Q-Network job can be executed on the FPGA of the Zynq board more than 26 times faster than with ARM Coretex-A9 650-MHz software.
Date of Conference: 07-09 December 2015
Date Added to IEEE Xplore: 28 January 2016
ISBN Information:
Conference Location: Queenstown, New Zealand

References

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