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cs.AI2026

Modular Discovery of General Game-Playing Algorithms with Large Language Models

Zun Li, John Schultz, Marc Lanctot +1

General Game Playing across arbitrary games from rules alone remains challenging due to differing algorithmic requirements across game classes and strict decision-time constraints.…

cs.AI2026

Game Arena: Strategic LLM Evaluation in Competitive Environments

Bovard Doerschuk-Tiberi, Yao Yan, Justin Chiu +59

We introduce Kaggle Game Arena, an open and ever-expanding platform to evaluate large language models (LLMs) through competitive games. Different from static benchmarks, game arena…

cs.AI2026

Active Evaluation of General Agents: Problem Definition and Comparison of Baseline Algorithms

Marc Lanctot, Kate Larson, Ian Gemp +1

As intelligent agents become more generally-capable, i.e. able to master a wide variety of tasks, the complexity and cost of properly evaluating them rises significantly. Tasks tha…

cs.AI2025

Code World Models for General Game Playing

Wolfgang Lehrach, Daniel Hennes, Miguel Lazaro-Gredilla +13

Large Language Models (LLMs) reasoning abilities are increasingly being applied to classical board and card games, but the dominant approach -- involving prompting for direct move…

cs.AI2025

Jackpot! Alignment as a Maximal Lottery

Roberto-Rafael Maura-Rivero, Marc Lanctot, Francesco Visin +1

Reinforcement Learning from Human Feedback (RLHF), the standard for aligning Large Language Models (LLMs) with human values, is known to fail to satisfy properties that are intuiti…