29 research outputs found

    Ludii -- The Ludemic General Game System

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    While current General Game Playing (GGP) systems facilitate useful research in Artificial Intelligence (AI) for game-playing, they are often somewhat specialised and computationally inefficient. In this paper, we describe the "ludemic" general game system Ludii, which has the potential to provide an efficient tool for AI researchers as well as game designers, historians, educators and practitioners in related fields. Ludii defines games as structures of ludemes -- high-level, easily understandable game concepts -- which allows for concise and human-understandable game descriptions. We formally describe Ludii and outline its main benefits: generality, extensibility, understandability and efficiency. Experimentally, Ludii outperforms one of the most efficient Game Description Language (GDL) reasoners, based on a propositional network, in all games available in the Tiltyard GGP repository. Moreover, Ludii is also competitive in terms of performance with the more recently proposed Regular Boardgames (RBG) system, and has various advantages in qualitative aspects such as generality.Comment: Accepted at ECAI 202

    A Practical introduction to the Ludii General Game System

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    Ludii is a new general game system, currently under development, which aims to support a wider range of games than existing systems and approaches. It is being developed primarily for the task of game design, but o↵ers a number of other potential benefits for game and AI researchers, professionals and hobbyists. This paper is based on an interactive demonstration of Ludii at thuis year’s Advances in Computer Games conference (ACG 2019). It describes the approach behind Ludii, how it works, how it is used, and what it can potentially do

    General Game Heuristic Prediction Based on Ludeme Descriptions

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    This paper investigates the performance of different general-game-playing heuristics for games in the Ludii general game system. Based on these results, we train several regression learning models to predict the performance of these heuristics based on each game's description file. We also provide a condensed analysis of the games available in Ludii, and the different ludemes that define them.Comment: 4 pages, 1 figure, 2 table

    Ludii as a Competition Platform

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    Ludii is a general game system being developed as part of the ERC-funded Digital Ludeme Project (DLP). While its primary aim is to model, play, and analyse the full range of traditional strategy games, Ludii also has the potential to support a wide range of AI research topics and competitions. This paper describes some of the future competitions and challenges that we intend to run using the Ludii system, highlighting some of its most important aspects that can potentially lead to many algorithm improvements and new avenues of research. We compare and contrast our proposed competition motivations, goals and frameworks against those of existing general game playing competitions, addressing the strengths and weaknesses of each platform

    An Empirical Evaluation of Two General Game Systems: Ludii and RBG

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    Although General Game Playing (GGP) systems can facilitate useful research in Artificial Intelligence (AI) for gameplaying, they are often computationally inefficient and somewhat specialised to a specific class of games. However, since the start of this year, two General Game Systems have emerged that provide efficient alternatives to the academic state of the art the Game Description Language (GDL). In order of publication, these are the Regular Boardgames language (RBG), and the Ludii system. This paper offers an experimental evaluation of Ludii. Here, we focus mainly on a comparison between the two new systems in terms of two key properties for any GGP system: simplicity/clarity (e.g. human-readability), and efficiency

    Measuring Board Game Distance

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    This paper presents a general approach for measuring distances between board games within the Ludii general game system. These distances are calculated using a previously published set of general board game concepts, each of which represents a common game idea or shared property. Our results compare and contrast two different measures of distance, highlighting the subjective nature of such metrics and discussing the different ways that they can be interpreted
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