Python Agent in Ludii
Izaias S. de Lima Neto (1), Marco A. A. de Aguiar Vieira (1), Anderson, R. Tavares (1) ((1) Instituto de Inform\'atica, Universidade Federal do Rio, Grande do Sul)

TL;DR
This paper introduces Python interfaces for Ludii, a Java-based general game system, enabling Python agent development and comparing the performance of different Java-Python integration libraries.
Contribution
It provides and evaluates Python interfaces for Ludii using jpy and Py4J, analyzing their performance for general game playing agents.
Findings
jpy is faster than Py4J for Ludii agent integration
Performance varies with game complexity and algorithm used
Regression models predict jpy's superior speed over Py4J
Abstract
Ludii is a Java general game system with a considerable number of board games, with an API for developing new agents and a game description language to create new games. To improve versatility and ease development, we provide Python interfaces for agent programming. This allows the use of Python modules to implement general game playing agents. As a means of enabling Python for creating Ludii agents, the interfaces are implemented using different Java libraries: jpy and Py4J. The main goal of this work is to determine which version is faster. To do so, we conducted a performance analysis of two different GGP algorithms, Minimax adapted to GGP and MCTS. The analysis was performed across several combinatorial games with varying depth, branching factor, and ply time. For reproducibility, we provide tutorials and repositories. Our analysis includes predictive models using regression,…
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Taxonomy
TopicsComputational Physics and Python Applications
