52 citations · 74 across the 9 of their papers we have counts for
16 papers
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…
PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games
Martin Balla, George E. M. Long, Dominik Jeurissen +3
In recent years, Game AI research has made important breakthroughs using Reinforcement Learning (RL). Despite this, RL for modern tabletop games has gained little to no attention,…
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…
"Did You Hear That?" Learning to Play Video Games from Audio Cues
Raluca D. Gaina, Matthew Stephenson
Game-playing AI research has focused for a long time on learning to play video games from visual input or symbolic information. However, humans benefit from a wider array of sensor…
Project Thyia: A Forever Gameplayer
Raluca D. Gaina, Simon M. Lucas, Diego Perez-Liebana
The space of Artificial Intelligence entities is dominated by conversational bots. Some of them fit in our pockets and we take them everywhere we go, or allow them to be a part of…
A Local Approach to Forward Model Learning: Results on the Game of Life Game
Simon M. Lucas, Alexander Dockhorn, Vanessa Volz +6
This paper investigates the effect of learning a forward model on the performance of a statistical forward planning agent. We transform Conway's Game of Life simulation into a sing…
Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best
Simon M. Lucas, Jialin Liu, Ivan Bravi +4
This paper introduces a simple and fast variant of Planet Wars as a test-bed for statistical planning based Game AI agents, and for noisy hyper-parameter optimisation. Planet Wars…
The Multi-Agent Reinforcement Learning in MalmÖ (MARLÖ) Competition
Diego Perez-Liebana, Katja Hofmann, Sharada Prasanna Mohanty +5
Learning in multi-agent scenarios is a fruitful research direction, but current approaches still show scalability problems in multiple games with general reward settings and differ…
General Video Game AI: a Multi-Track Framework for Evaluating Agents, Games and Content Generation Algorithms
Diego Perez-Liebana, Jialin Liu, Ahmed Khalifa +3
General Video Game Playing (GVGP) aims at designing an agent that is capable of playing multiple video games with no human intervention. In 2014, The General Video Game AI (GVGAI)…
The N-Tuple Bandit Evolutionary Algorithm for Automatic Game Improvement
Kamolwan Kunanusont, Raluca D. Gaina, Jialin Liu +2
This paper describes a new evolutionary algorithm that is especially well suited to AI-Assisted Game Design. The approach adopted in this paper is to use observations of AI agents…
Analysis of Vanilla Rolling Horizon Evolution Parameters in General Video Game Playing
Raluca D. Gaina, Jialin Liu, Simon M. Lucas +1
Monte Carlo Tree Search techniques have generally dominated General Video Game Playing, but recent research has started looking at Evolutionary Algorithms and their potential at ma…
Population Seeding Techniques for Rolling Horizon Evolution in General Video Game Playing
Rauca D. Gaina, Simon M. Lucas, Diego Perez-Liebana
While Monte Carlo Tree Search and closely related methods have dominated General Video Game Playing, recent research has demonstrated the promise of Rolling Horizon Evolutionary Al…