17 citations · 21 across the 3 of their papers we have counts for
11 papers · 1 filter
From Code to Play: Benchmarking Program Search for Games Using Large Language Models
Manuel Eberhardinger, James Goodman, Alexander Dockhorn +5
Large language models (LLMs) have shown impressive capabilities in generating program code, opening exciting opportunities for applying program synthesis to games. In this work, we…
PyTAG: Tabletop Games for Multi-Agent Reinforcement Learning
Martin Balla, George E. M. Long, James Goodman +2
Modern Tabletop Games present various interesting challenges for Multi-agent Reinforcement Learning. In this paper, we introduce PyTAG, a new framework that supports interacting wi…
Design and Implementation of TAG: A Tabletop Games Framework
Raluca D. Gaina, Martin Balla, Alexander Dockhorn +2
This document describes the design and implementation of the Tabletop Games framework (TAG), a Java-based benchmark for developing modern board games for AI research. TAG provides…
Rolling Horizon NEAT for General Video Game Playing
Diego Perez-Liebana, Muhammad Sajid Alam, Raluca D. Gaina
This paper presents a new Statistical Forward Planning (SFP) method, Rolling Horizon NeuroEvolution of Augmenting Topologies (rhNEAT). Unlike traditional Rolling Horizon Evolution,…
Rolling Horizon Evolutionary Algorithms for General Video Game Playing
Raluca D. Gaina, Sam Devlin, Simon M. Lucas +1
Game-playing Evolutionary Algorithms, specifically Rolling Horizon Evolutionary Algorithms, have recently managed to beat the state of the art in win rate across many video games.…
Learning Local Forward Models on Unforgiving Games
Alexander Dockhorn, Simon M. Lucas, Vanessa Volz +3
This paper examines learning approaches for forward models based on local cell transition functions. We provide a formal definition of local forward models for which we propose two…