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Ludii is intended as a general purpose tool for anyone interested in games: AI researchers, historians, designers, hobbyists, … We hope to eventually provide the following services (future work!).



Ludii will support the following modes of play.

- Human-AI: Play any game against the default Ludii AI agents or your own custom AIs.

- Human-Human: Play remotely against other players through a network connection.

- AI-AI: Watch the AIs battle it out!

- Tournament: Set up your own tournaments to evaluate a number of AI agents for a particular game or set of games. Test AI playing strength over a range of games against a range of opponents.

- Solve: Check puzzles and other CSP-style problems for solvability, uniqueness and deducibility.



We will provide automatic evaluations of games, typically based on self-play trials, either directly through Ludii or upon request through the Ludii Portal.

- Evaluate games for playability based on simple but reliable metrics.

- Evaluate games for quality based on preferred aesthetic criteria.

- Estimate the strategic depth of games.

- Estimate the historical authenticity of rule sets based on the historical and cultural evidence contained in the game library [link].

- Explore coalition effects in multiplayer games.

- Provide comprehensible explanations of learnt strategies.

- Data mine the game library to find common ludemeplexes (structures of ludemes) across the full range of games.

- Cluster games by ludemeplex to find new classifications based on implicit mechanisms of play.

- Provide mathematical profiles of games, based on mathematical concepts associated with each ludeme.

- Provide plain English rule descriptions based on ludemic descriptions.

- Estimate conceptual distance between given games, for phylogenetic analysis and novelty/plagiarism testing.



We will provide a number of automated game design and optimisation services, either directly through Ludii or upon request through the Ludii Portal.

- Complete plausible rule sets from partial evidence based on historical and cultural context.

- Optimise known reconstructions to maximise game quality and historical authenticity.

- Find interesting new games similar to a known base game.

- Generate new games through unconstrained search or targetted at specific criteria.

- Generate bespoke games based on player preferences.

- Suggest similar games that players might like.

- Generate puzzles from games to demonstrate particular aspects.


     Contact Us

lkjh Maastricht University Department of Advanced Computing Sciences (DACS), Paul-Henri Spaaklaan 1, 6229 EN Maastricht, Netherlands Funded by a €2m ERC Consolidator Grant (#771292) from the European Research Council