Abstract
The speed of game rules processing plays an essential role in the performance of a General Game Playing (GGP) agent. Propositional Networks (propnets) are an example of a highly efficient representation of game rules. So far, in GGP, only software implementations of propnets have been proposed and investigated. In this paper, we present the first implementation of propnets on Field-Programmable Gate Arrays (FPGAs), showing that they perform between 25 and 58 times faster than a software-propnet for most of the tested games. We also integrate the FPGA-propnet within an MCTS agent, discussing the challenges of the process, and possible solutions for the identified shortcomings.
J. Kowalski—Supported in part by the National Science Centre, Poland under project number 2015/17/B/ST6/01893.
C. F. Sironi—Supported by the Netherlands Organisation for Scientific Research (NWO) under the GoGeneral project, grant number 612.001.121.
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Siwek, C., Kowalski, J., Sironi, C.F., Winands, M.H.M. (2018). Implementing Propositional Networks on FPGA. In: Mitrovic, T., Xue, B., Li, X. (eds) AI 2018: Advances in Artificial Intelligence. AI 2018. Lecture Notes in Computer Science(), vol 11320. Springer, Cham. https://doi.org/10.1007/978-3-030-03991-2_14
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