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Found 24 papers, 6 papers with code
Measuring Board Game Distance
This paper presents a general approach for measuring distances between board games within the Ludii general game system.
Combining Monte-Carlo Tree Search with Proof-Number Search
Proof-Number Search (PNS) and Monte-Carlo Tree Search (MCTS) have been successfully applied for decision making in a range of games.
The Ludii Game Description Language is Universal
There are several different game description languages (GDLs), each intended to allow wide ranges of arbitrary games (i. e., general games) to be described in a single higher-level language than general-purpose programming languages.
Spatial State-Action Features for General Games
In many board games and other abstract games, patterns have been used as features that can guide automated game-playing agents.
General Board Geometry
Game boards are described in the Ludii general game system by their underlying graphs, based on tiling, shape and graph operators, with the automatic detection of important properties such as topological relationships between graph elements, directions and radial step sequences.
Optimised Playout Implementations for the Ludii General Game System
This paper describes three different optimised implementations of playouts, as commonly used by game-playing algorithms such as Monte-Carlo Tree Search.
Automatic Generation of Board Game Manuals
In this paper we present a process for automatically generating manuals for board games within the Ludii general game system.
General Board Game Concepts
Many games often share common ideas or aspects between them, such as their rules, controls, or playing area.
General Game Heuristic Prediction Based on Ludeme Descriptions
This paper investigates the performance of different general-game-playing heuristics for games in the Ludii general game system.
Transfer of Fully Convolutional Policy-Value Networks Between Games and Game Variants
In this paper, we use fully convolutional architectures in AlphaZero-like self-play training setups to facilitate transfer between variants of board games as well as distinct games.
Deep Learning for General Game Playing with Ludii and Polygames
Combinations of Monte-Carlo tree search and Deep Neural Networks, trained through self-play, have produced state-of-the-art results for automated game-playing in many board games.
Ludii Game Logic Guide
This technical report outlines the fundamental workings of the game logic behind Ludii, a general game system, that can be used to play a wide variety of games.
Strategic Features for General Games
This short paper describes an ongoing research project that requires the automated self-play learning and evaluation of a large number of board games in digital form.
Modern Techniques for Ancient Games
Games potentially provide a wealth of knowledge about our shared cultural past and the development of human civilisation, but our understanding of early games is incomplete and often based on unreliable reconstructions.
Manipulating the Distributions of Experience used for Self-Play Learning in Expert Iteration
ExIt involves training a policy to mimic the search behaviour of a tree search algorithm - such as Monte-Carlo tree search - and using the trained policy to guide it.
Ludii as a Competition Platform
Ludii is a general game system being developed as part of the ERC-funded Digital Ludeme Project (DLP).
Ludii and XCSP: Playing and Solving Logic Puzzles
Many of the famous single-player games, commonly called puzzles, can be shown to be NP-Complete.
An Empirical Evaluation of Two General Game Systems: Ludii and RBG
Although General Game Playing (GGP) systems can facilitate useful research in Artificial Intelligence (AI) for game-playing, they are often computationally inefficient and somewhat specialised to a specific class of games.
An Overview of the Ludii General Game System
The Digital Ludeme Project (DLP) aims to reconstruct and analyse over 1000 traditional strategy games using modern techniques.
Foundations of Digital Archæoludology
Digital Archaeoludology (DAL) is a new field of study involving the analysis and reconstruction of ancient games from incomplete descriptions and archaeological evidence using modern computational techniques.
Learning Policies from Self-Play with Policy Gradients and MCTS Value Estimates
In recent years, state-of-the-art game-playing agents often involve policies that are trained in self-playing processes where Monte Carlo tree search (MCTS) algorithms and trained policies iteratively improve each other.
Ludii -- The Ludemic General Game System
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.
Improved Reinforcement Learning with Curriculum
Humans tend to learn complex abstract concepts faster if examples are presented in a structured manner.
Biasing MCTS with Features for General Games
This paper proposes using a linear function approximator, rather than a deep neural network (DNN), to bias a Monte Carlo tree search (MCTS) player for general games.
