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Game Data

How might we analyse the big data exhausts of games to support game developers and understand people inside and outside of games?


Project areas include:

  • Imitation Learning: Using game data from human players we can build AI opponents and team-mates to enhance multi-player games.

  • Comparative Analysis of Games: By comparing data across different games, developers can understand key factors underlying game genres or mechanics, leading to more successful future game designs.

  • Social Dynamics in Games: Studying data from multiplayer games can uncover fascinating insights about social dynamics and cooperation/competition among players.

  • Game Economics: In games with virtual economies, tracking and analysing economic data can help maintain balanced economies, which is crucial for player satisfaction and the longevity of the game.


iGGi >>> People <<< relevant to this Theme:

Dominik Jeurissen

Dominik Jeurissen

iGGi PG Researcher

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Game AI, Design & Development, Game Data

Dr Alan Pedrassoli Chitayat

Dr Alan Pedrassoli Chitayat

iGGi Alum

Available for post-PhD position

Design & Development, Game Data, Esports

Dr Charles Ringer

Dr Charles Ringer

iGGi Alum

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Game AI, Game Data, Esports

Sunny Thaicharoen

Sunny Thaicharoen

iGGi PG Researcher

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Player Research, Game Data, Esports

George Long

George Long

iGGi PG Researcher

Available for placement

Game AI, Design & Development, Game Data

Dr Diego Pérez-Liébana

Dr Diego Pérez-Liébana

Supervisor

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Game AI, Game Data

Dr Oliver Scholten

Dr Oliver Scholten

iGGi Alum

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Game Data

Dr Ozan Vardal

Dr Ozan Vardal

iGGi Alum

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Design & Development, Game Data, Esports

Dr Cade McCall

Dr Cade McCall

Supervisor

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Applied Games, Game Data, Player Research

Dr Søren Riis

Dr Søren Riis

Supervisor

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Game AI, Game Data, Creative Computing

Dr Florence Smith Nicholls

Dr Florence Smith Nicholls

iGGi Alum

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Game AI, Creative Computing, Design & Development, Game Data

Prof. Alex Wade

Prof. Alex Wade

Supervisor

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Player Research, Applied Games, Creative Computing, Game Data, Esports

iGGi >>> Publications <<< relevant to this Theme:

Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds

R Sasso, M Conserva, D Jeurissen, P Rauber

arXiv preprint arXiv:2509.15915, 2025

Archaeological Gameworld Affordances: A Grounded Theory of How Players Interpret Environmental Storytelling

F Smith Nicholls, M Cook

CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, Article no 465, p. 1 - 20

CG-TTRL: Context-Guided Test-Time Reinforcement Learning for On-Device Large Language Models

P Hosseini, O Bohdal, T Ceritli, I Castro, M Purver, M Ozay, U Michieli

arXiv preprint arXiv:2511.06430, 2025

Exploration with Foundation Models: Capabilities, Limitations, and Hybrid Approaches

R Sasso, M Conserva, D Jeurissen, P Rauber

arXiv preprint arXiv:2509.19924, 2025

Applying machine learning to enhance esport broadcast narratives

A Pedrassoli Chitayat

University of York, 2025

Playing NetHack with LLMs: Potential & Limitations as Zero-Shot Agents

D Jeurissen, D Perez-Liebana, J Gow, D Cakmak, J Kwan

arXiv preprint arXiv:2403.00690, 2024

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The EPSRC Centre for Doctoral Training in Intelligent Games and Game Intelligence (iGGi) is a leading PhD research programme aimed at the Games and Creative Industries.

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