The ‘AI and Games Conference’ brings together developers from across the games industry alongside academic researchers to learn, network and discuss applications of artificial intelligence for video games. We invite you to join us for two tracks of talks detailing how AI is used within, and to support production in the video games industry, alongside ground-breaking research, and relevant insights into broader business development within the field.
Our conference is broken down into two tracks: ‘AI for Gameplay’, and ‘AI for Production’. Given the breadth of AI technologies, methodologies and implementations in the industry, this allows us to curate our talks and for our attendees to focus on the areas that matter to them most.
The AI and Games Conference is a collaboration between AI and Games Ltd and Game AI Events CIC – a UK-based non-profit – that seeks to provide an accessible, high-quality event for game AI practitioners based in the UK and Europe.
Our Partner Sponsors
Event Sponsors
Our Organisational Partners
Alessandro Sestini is a research engineer at SEED - Electronic Arts. SEED is a R&D lab within Electronic Arts - a pioneering group combining creativity with applied research. Alessandro obtained his PhD with honorable mention in Smart Computing and Computer Engineering, at Università degli Studi di Firenze, Florence under the supervision of prof Andrew Bagdanov (ex Westwood Studios); Alessandro is currently working on how to apply Deep Reinforcement Learning, Inverse Reinforcement Learning, Imitation Learning and Large Language Models for video game production, helping video game industry in the use of machine learning. His goal is to train/develop intelligent agents for game AI and playtesting.
Alessandro contributed to the game AI landscape publishing several academic papers and giving several talks about the intersection between machine learning and video game development, helping researchers and practitioners in adopting such technology. He is the solo developer of DeepCrawl, a turn-based roguelike game for mobile devices where the NPCs are controlled by machine learning. Alessandro obtained his master degree with honorable mention in computer engineering working on using Machine Learning for the development of AI in roguelike games.
Alessandro Sestini is a research engineer at SEED - Electronic Arts. SEED is a R&D lab within Electronic Arts - a pioneering group combining creativity with applied research. Alessandro obtained his PhD with honorable mention in Smart Computing and Computer Engineering, at Università degli Studi di Firenze, Florence under the supervision of prof Andrew Bagdanov (ex Westwood Studios); Alessandro is currently working on how to apply Deep Reinforcement Learning, Inverse Reinforcement Learning, Imitation Learning and Large Language Models for video game production, helping video game industry in the use of machine learning. His goal is to train/develop intelligent agents for game AI and playtesting.
Alessandro contributed to the game AI landscape publishing several academic papers and giving several talks about the intersection between machine learning and video game development, helping researchers and practitioners in adopting such technology. He is the solo developer of DeepCrawl, a turn-based roguelike game for mobile devices where the NPCs are controlled by machine learning. Alessandro obtained his master degree with honorable mention in computer engineering working on using Machine Learning for the development of AI in roguelike games.
Breton has been working in the game industry for more than 15 years now. Starting on pathfinding and animation middleware, and later moving to production as an AI/Gameplay programmer. Breton is currently AI Lead on 'Last Expedition', a PVPVE Extraction game.
Breton has been working in the game industry for more than 15 years now. Starting on pathfinding and animation middleware, and later moving to production as an AI/Gameplay programmer. Breton is currently AI Lead on 'Last Expedition', a PVPVE Extraction game.
Dr Christoph Salge is a Reader in Artificial Intelligence in Games at the University of Hertfordshire. His research interests span topics such as games, artificial intelligence, intrinsic motivation, procedural content generation, robotics and artificial life - focused on the big question of how we will design a future human-AI society. He is an avid gamer of computer-, board- and roleplaying games, and the main organizer of the AI Settlement Generation Challenge in Minecraft.
Dr Christoph Salge is a Reader in Artificial Intelligence in Games at the University of Hertfordshire. His research interests span topics such as games, artificial intelligence, intrinsic motivation, procedural content generation, robotics and artificial life - focused on the big question of how we will design a future human-AI society. He is an avid gamer of computer-, board- and roleplaying games, and the main organizer of the AI Settlement Generation Challenge in Minecraft.
Dr. Diego Perez-Liebana (he/him/his) is the co-founder and director of Tabletop R&D, and currently a Senior Lecturer in Computer Games and Artificial Intelligence at Queen Mary University of London (UK). He holds a Ph.D in Computer Science from the University of Essex (2015). His research is centered in the application of Artificial Intelligence to games, Tree Search and Evolutionary Computation, and he’s especially interested in the application of Statistical Forward Planning methods to modern games, in particular to modern Tabletop Board Games. He is author of more than 100 papers in the field of Game AI and has experience in the games industry as a game programmer and AI tool developer.
Dr. Diego Perez-Liebana (he/him/his) is the co-founder and director of Tabletop R&D, and currently a Senior Lecturer in Computer Games and Artificial Intelligence at Queen Mary University of London (UK). He holds a Ph.D in Computer Science from the University of Essex (2015). His research is centered in the application of Artificial Intelligence to games, Tree Search and Evolutionary Computation, and he’s especially interested in the application of Statistical Forward Planning methods to modern games, in particular to modern Tabletop Board Games. He is author of more than 100 papers in the field of Game AI and has experience in the games industry as a game programmer and AI tool developer.
After completing a masters in computing science at in the Bionic Limbs for Improved Natural Control (BLINC) Lab at University of Alberta, Jaden went on to lead a research team at Eidos-Montreal applying Reinforcement Learning (RL) to functional game testing, developing several internal and open source tools. Jaden then went on to work as an AI Engineer at Sony AI, contributing to the training and game integration of Gran Turismo Sophy on PS5.
After completing a masters in computing science at in the Bionic Limbs for Improved Natural Control (BLINC) Lab at University of Alberta, Jaden went on to lead a research team at Eidos-Montreal applying Reinforcement Learning (RL) to functional game testing, developing several internal and open source tools. Jaden then went on to work as an AI Engineer at Sony AI, contributing to the training and game integration of Gran Turismo Sophy on PS5.
Mónica Villanueva Aylagas is a Research Engineer at SEED, an applied research and innovation group within Electronic Arts. Working in the intersection of cutting-edge technology and art, Monica's focus and interest is in generative models and how they can help creative people unlock their potential.
With 6 years of experience in the gaming industry, Mónica has been instrumental in the development and adoption of ML driven technologies such as Voice2Face, Exflowsions and Avalon.
Mónica holds a Bachelor’s degree in Computer Science Engineering from the Autonomous University of Madrid and a Master’s degree in Machine Learning from KTH in Stockholm.
Mónica Villanueva Aylagas is a Research Engineer at SEED, an applied research and innovation group within Electronic Arts. Working in the intersection of cutting-edge technology and art, Monica's focus and interest is in generative models and how they can help creative people unlock their potential.
With 6 years of experience in the gaming industry, Mónica has been instrumental in the development and adoption of ML driven technologies such as Voice2Face, Exflowsions and Avalon.
Mónica holds a Bachelor’s degree in Computer Science Engineering from the Autonomous University of Madrid and a Master’s degree in Machine Learning from KTH in Stockholm.
Oleksandr has been Interested in computers and computer games since childhood. While studying a degree in Software Engineer, he uncovered a deeper passion in mathematics and performant low-level programming; leading to career in game physics, and later the development of AI tech for games.
Oleksandr has been Interested in computers and computer games since childhood. While studying a degree in Software Engineer, he uncovered a deeper passion in mathematics and performant low-level programming; leading to career in game physics, and later the development of AI tech for games.
Dr. Raluca D. Gaina (she/her/hers) is the co-founder and director of Tabletop R&D, and is currently a Lecturer in Game AI at Queen Mary University of London, where she obtained her Ph.D. in Intelligent Games and Games Intelligence. She has led innovative research in Simulation-Based decision-making and modern Tabletop Games, laying the foundation for the Tabletop Games Framework (TAG). She has co-organised top Game AI conferences, meetups, tutorials and competitions. She has over 30 publications in leading Game AI conferences (AAAI, COG) and journals (TOG), and received multiple awards for her public engagement videos. Her research interests include general video game playing AI, evolutionary algorithms and tabletop games.
Dr. Raluca D. Gaina (she/her/hers) is the co-founder and director of Tabletop R&D, and is currently a Lecturer in Game AI at Queen Mary University of London, where she obtained her Ph.D. in Intelligent Games and Games Intelligence. She has led innovative research in Simulation-Based decision-making and modern Tabletop Games, laying the foundation for the Tabletop Games Framework (TAG). She has co-organised top Game AI conferences, meetups, tutorials and competitions. She has over 30 publications in leading Game AI conferences (AAAI, COG) and journals (TOG), and received multiple awards for her public engagement videos. Her research interests include general video game playing AI, evolutionary algorithms and tabletop games.
Will is the AI Lead for Ara: History Untold, a 4X grand strategy game from Oxide Games, and a PhD student at the University of Maryland, studying applied machine learning for digital content creation. He has a passion for making new things, especially in the realm of creative tools. The intersection of challenging technical problems and art is endlessly fascinating, and feels lucky every day to get to work in it! Beyond work, he enjoys spending time with their lovely partner, travel, running, and World of Warcraft (Blood and Thunder)
Will is the AI Lead for Ara: History Untold, a 4X grand strategy game from Oxide Games, and a PhD student at the University of Maryland, studying applied machine learning for digital content creation. He has a passion for making new things, especially in the realm of creative tools. The intersection of challenging technical problems and art is endlessly fascinating, and feels lucky every day to get to work in it! Beyond work, he enjoys spending time with their lovely partner, travel, running, and World of Warcraft (Blood and Thunder)
Alan Zucconi is a Senior Lecturer, author and a passionate developer focused on the field of education. As a Science Communicator he is investigating the impact that AI has on society, from deepfakes to algorithmic bias. He currently works at Goldsmiths, University of London as Director of Postgraduate Studies, where he also directs the MA/MSc Computer Games programmes.
Alan Zucconi is a Senior Lecturer, author and a passionate developer focused on the field of education. As a Science Communicator he is investigating the impact that AI has on society, from deepfakes to algorithmic bias. He currently works at Goldsmiths, University of London as Director of Postgraduate Studies, where he also directs the MA/MSc Computer Games programmes.
Duygu Cakmak is the R&D Director at Creative Assembly for the BAFTA award-winning Total War series. She oversees the R&D strategy and direction for the franchise. She joined Creative Assembly in 2015 as an AI programmer and after this, she moved into a Project Technical Director role.
Duygu Cakmak is the R&D Director at Creative Assembly for the BAFTA award-winning Total War series. She oversees the R&D strategy and direction for the franchise. She joined Creative Assembly in 2015 as an AI programmer and after this, she moved into a Project Technical Director role.
Gabriel Robert has been working as a Game AI Developer since 1999 on many franchises, including Top Spin, Ghost Recon, and Assassin's Creed.
Since earning his PhD in 2005, his goal has been to bridge the gap between academic research and production, a pursuit he now fulfills as a lead R&D Developer.
As a strong believer in knowledge sharing as a foundation for innovation, Gabriel naturally chose to join the AI and Games Conference team.
Gabriel Robert has been working as a Game AI Developer since 1999 on many franchises, including Top Spin, Ghost Recon, and Assassin's Creed.
Since earning his PhD in 2005, his goal has been to bridge the gap between academic research and production, a pursuit he now fulfills as a lead R&D Developer.
As a strong believer in knowledge sharing as a foundation for innovation, Gabriel naturally chose to join the AI and Games Conference team.
George is the creator of Video Games Industry Memo and founder of Half-Space Consulting: a strategic consultancy that supports businesses as they seek to work within the video games industry.
George is the creator of Video Games Industry Memo and founder of Half-Space Consulting: a strategic consultancy that supports businesses as they seek to work within the video games industry.
Matthias is the head of AI at Splash Damage, and has worked as a programmer on titles including 'Sacred 3', 'Portal Knights', and was the AI lead on 'Gears Tactics'.
Matthias is the head of AI at Splash Damage, and has worked as a programmer on titles including 'Sacred 3', 'Portal Knights', and was the AI lead on 'Gears Tactics'.
Tommy is the director of 'AI and Games' which provides development, consultancy, and professional training services for artificial intelligence in the video games industry.
With 20 years experience in AI for video games, Tommy has become a trusted voice in the game AI community as he acts as a public speaker, science communicator, and industry advocate. His work is bolstered by his successful YouTube series 'AI and Games', that has accrued millions of views since it began in 2014.
Tommy is the director of 'AI and Games' which provides development, consultancy, and professional training services for artificial intelligence in the video games industry.
With 20 years experience in AI for video games, Tommy has become a trusted voice in the game AI community as he acts as a public speaker, science communicator, and industry advocate. His work is bolstered by his successful YouTube series 'AI and Games', that has accrued millions of views since it began in 2014.
Schedule
We'll be updating our schedule with more speakers and talks in the coming weeks!
- Thursday 7th November
- Friday 8th November
- Speaker/Sponsor Reception
A drinks reception for our speakers and sponsors to network, test their talks in the venue, and grab their passes prior to the big event!
- AI for Gameplay
- AI for Production
Description:
Description: Last Expedition is a PvPvE extraction shooter currently in playable alpha. In this walk we explore how we have implemented Goal Oriented Action Planning (GOAP) for our bot behaviours. In this presentation we will give more detail on the implementation challenges faced when building the system in Unreal Engine, and go into aspects that are still rather abstract from the original papers. This talk will explain why it’s a great method for bots that have objects, and how game designers can add new goals or tweak behaviours easily via blueprints.
Takeaways:
- Under how to implement GOAP in Unreal Engine
- Highlight the value of visual debugging within Unreal for AI behaviour.
- Understand how adding new features for NPC abilities in GOAP is relatively easy.
Description: Computing the position of objects in a game is one of the most frequent features to be carried out: where to stop a movement (to avoid a collision)? Where to hide, protect or start a jump? Where do two zones intersect (which objects will be affected by the zone of effect of my action)?
The goal of this presentation is to suggest that solving the analytical geometry equations resulting from the various game situations is preferable to using the various environment projection queries provided by your favourite game engine: first write the equations to which the coordinates of the game objects must conform, then solve these equations to obtain the numerical values of these coordinates; and don’t forget to get help from a math software. These two steps will be illustrated in the case of projecting a grid onto a navigation surface for the Unreal Engine with the help of Mathematica.
Takeaways: This presentation is intended for AI game developers facing one of the three situations:
- Too much computing resources are spent generating sample locations and then filtering them
- Write and solve the equations modelling the geometric problem
- Too many erroneous or approximate locations require post-processing to be usable
- Compute values from exact solutions of your geometric problems
- Bullet proofs tests of locations are needed
- Compare locations with exact solutions of your geometric equations
Description: The talk covers the solution of AI pathfinding problem in modern game engines with the help of a navigation mesh (navmesh). Applying a navmesh to your games is seldom a straightforward task, so we discuss the best practices of how to get the most out of the navigation pipline, and what aspects of the tools you need to be aware of to resolve your design challenges.
Takeaways:
- 1. How to choose the right tool for a particular pathfinding problem.
- 2. What is a navmesh and how it’s used in games.
- 3. A brief overview of the recast navigation library
Description: A continuation and recontextualization of my 2024 GDC AI Summit talk “How ‘Ara: History Untold’ Transformed AI in 4X Games”, I will summarize Ara: History Untold’s novel system, and dig into details around optimizing its performance, and usability in the final months leading up to ship.
Takeaways:
- An introduction to semi-obscure but very useful AI topics (HGNs, Logical DSLs)
- Insights into making performant data structures for complex game AI
- Practical examples of how to make trades between effectiveness and complexity
Description: Avalon is a new method designed to enhance level generation by providing more control over the generation process, while ensuring the creation of more solvable levels. In particular, we generate layouts of match-3 levels where the level designers can select visual features like size and symmetry and gameplay statistics such as difficulty. We will describe how we designed the system, how it compares to other methods and the quantitative and qualitative analysis performed on it. We will finalize with a brief discussion about challenges and opportunities of level generators in production.
Takeaways:
- How to create controllable (conditional) generators for match3 games
- How to take advantage of that controllability to improve the validity of the levels
- Challenges and opportunities of level generators in production
Description: What are the challenges in writing an AI that can generate an interesting settlement adapted to an unseen Minecraft map? What AI techniques work well here? These are just some of the questions the GDMC AI settlement generation challenge set out to answer when it was founded 7 years ago. Adaptive and holistic procedural content generation in games still has many open challenges, and in this talk we will take a look at some selected ideas and AI techniques used to tackle those. I will show a range of colorful and amazing settlement generators, and discuss what worked and what did not. If you feel after the talk that you could do better, I have great news for you, we will be back in 2025 for round 8.
Takeaways:
- Learning about the GDMC competition – a fun AI programming competition.
- The use of AI competition to drive research and find out things.
- A comparison of different AI approaches to the same problem.
- A better understanding of the problems of adaptive PCG.
Description: The complexity of modern tabletop games has been steadily increasing since the mid-1990s. This results in an increase in time spent by designers developing (2-3 years on average from idea to commercialisation) and playtesting (6-24 months) a game, raising the barrier of entry to market for independent designers or small companies which do not have enough resources at their disposal. The effect is also felt by players, who find it harder to play such games due to the steep learning curve. This talk will explore how Tabletop R&D, a spin-out company from Queen Mary University of London, aims to address these issues and democratize the tabletop games market by providing game designers with automatic playtesting tools. Using the latest in Game AI technology and digital twins of tabletop games, we speed up development times, reduce costs and increase efficiency of an otherwise traditionally lengthy analogue process.
Takeaways:
- How to use automatic play-testing with AI agents.
- Learn about a diverse set of metrics to evaluate game-play experience.
- The value of exploring the design space of your game.
Description: Training RL agents in games requires collecting lots of data from various game states and trajectories. As games grow in complexity, it is easy for some unintended functionality to affect the distribution of data that an RL agent would be trained on. This means an agent’s behaviour may be affected and ultimately be a signal that some property of the game does not match intentions. This matches the criteria for a property based test and is an inspiration for future game testing mechanisms.
Takeaways:
- An intuition of property based testing.
- A concrete example of how RL training helped identify a bug
- An inspiration for how RL training can be more incorporated into property tests
Description: The Battlefield QV department manages an automated issue workflow that handles reports coming from diverse data sources and entities, such as error APIs, automation systems, etc. An important part of this workflow is the interaction with the issue tracking manager Jira, where tickets are created automatically using data retrieved from the reports. The process is not fully automated, as there are still parts that require the hardcoding of rules that may change over time or a manual intervention that can become time consuming when the volume of tickets reaches high peaks. The talk explores the potential of Large Language Models (LLMs) in automated issue management within the Battlefield franchise. It has the goal to address the identification of duplicate issues, replacing the inefficiency of the previous hardcoded rules. We will demonstrate how the same solution based on LLMs could also be reused in all the projects utilizing the same version of Frostbite (our engine). Furthermore, the talk discusses the challenges and best practices of integrating a research project into an established game development workflow, and how to overcome these challenges.
Takeaways:
- How to leverage the potential of LLMs for specific use cases in game development, particularly in QA.
- Insights into real-world QA improvements achieved through the use of LLMs compared to traditional approaches, along with the challenges in measuring these improvements.
- An understanding of the challenges and opportunities associated with using machine learning in game production, and how to effectively combine research and development efforts.
