143 citations · 781 across the 60 of their papers we have counts for
67 papers
Causal Supervision of Attention for Affective Behaviour Analysis
Nemanja Rašajski, Konstantinos Makantasis, Antonios Liapis +1
The \textit{11th Affective Behaviour Analysis in-the-wild Competition} includes the Multi-Task Learning Challenge, where participants develop a unified framework for Valence-Arousa…
Agents' Last Exam
Yiyou Sun, Xinyang Han, Weichen Zhang +355
Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…
Learning Local Constraints for Reinforcement-Learned Content Generators
Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis +1
Constraint-based game content generators that learn local constraints from existing content, such as Wave Function Collapse (WFC), can generate visually satisfying game levels but…
PREFAB: PREFerence-based Affective Modeling for Low-Budget Self-Annotation
Jaeyoung Moon, Youjin Choi, Yucheon Park +3
Self-annotation is the gold standard for collecting affective state labels in affective computing. Existing methods typically rely on full annotation, requiring users to continuous…
Emotions as Ambiguity-aware Ordinal Representations
Jingyao Wu, Matthew Barthet, David Melhart +1
Emotions are inherently ambiguous and dynamic phenomena, yet existing continuous emotion recognition approaches either ignore their ambiguity or treat ambiguity as an independent a…
Ethical Considerations of Large Language Models in Game Playing
Qingquan Zhang, Yuchen Li, Bo Yuan +3
Large language models (LLMs) have demonstrated tremendous potential in game playing, while little attention has been paid to their ethical implications in those contexts. This work…
Privileged Contrastive Pretraining for Multimodal Affect Modelling
Kosmas Pinitas, Konstantinos Makantasis, Georgios N. Yannakakis
Affective Computing (AC) has made significant progress with the advent of deep learning, yet a persistent challenge remains: the reliable transfer of affective models from controll…
Evolutionary Level Repair
Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis +1
We address the problem of game level repair, which consists of taking a designed but non-functional game level and making it functional. This might consist of ensuring the complete…
The Procedural Content Generation Benchmark: An Open-source Testbed for Generative Challenges in Games
Ahmed Khalifa, Roberto Gallotta, Matthew Barthet +3
This paper introduces the Procedural Content Generation Benchmark for evaluating generative algorithms on different game content creation tasks. The benchmark comes with 12 game-re…
Can Large Language Models Capture Video Game Engagement?
David Melhart, Matthew Barthet, Georgios N. Yannakakis
Can out-of-the-box pretrained Large Language Models (LLMs) detect human affect successfully when observing a video? To address this question, for the first time, we evaluate compre…
FREYR: A Framework for Recognizing and Executing Your Requests
Roberto Gallotta, Antonios Liapis, Georgios N. Yannakakis
Large language models excel as conversational agents, but their capabilities can be further extended through tool usage, i.e.: executable code, to enhance response accuracy or addr…
Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors
Niels Justesen, Maria Kaselimi, Sam Snodgrass +12
Artificial intelligence (AI) has enabled agents to master complex video games, from first-person shooters like Counter-Strike to real-time strategy games such as StarCraft II and r…
Across-Game Engagement Modelling via Few-Shot Learning
Kosmas Pinitas, Konstantinos Makantasis, Georgios N. Yannakakis
Domain generalisation involves learning artificial intelligence (AI) models that can maintain high performance across diverse domains within a specific task. In video games, for in…
Affectively Framework: Towards Human-like Affect-Based Agents
Matthew Barthet, Roberto Gallotta, Ahmed Khalifa +2
Game environments offer a unique opportunity for training virtual agents due to their interactive nature, which provides diverse play traces and affect labels. Despite their potent…
Closing the Affective Loop via Experience-Driven Reinforcement Learning Designers
Matthew Barthet, Diogo Branco, Roberto Gallotta +2
Autonomously tailoring content to a set of predetermined affective patterns has long been considered the holy grail of affect-aware human-computer interaction at large. The experie…
GameVibe: A Multimodal Affective Game Corpus
Matthew Barthet, Maria Kaselimi, Kosmas Pinitas +3
As online video and streaming platforms continue to grow, affective computing research has undergone a shift towards more complex studies involving multiple modalities. However, th…
Dynamic Quality-Diversity Search
Roberto Gallotta, Antonios Liapis, Georgios N. Yannakakis
Evolutionary search via the quality-diversity (QD) paradigm can discover highly performing solutions in different behavioural niches, showing considerable potential in complex real…
MAP-Elites with Transverse Assessment for Multimodal Problems in Creative Domains
Marvin Zammit, Antonios Liapis, Georgios N. Yannakakis
The recent advances in language-based generative models have paved the way for the orchestration of multiple generators of different artefact types (text, image, audio, etc.) into…
Large Language Models and Games: A Survey and Roadmap
Roberto Gallotta, Graham Todd, Marvin Zammit +4
Recent years have seen an explosive increase in research on large language models (LLMs), and accompanying public engagement on the topic. While starting as a niche area within nat…
BehAVE: Behaviour Alignment of Video Game Encodings
Nemanja Rašajski, Chintan Trivedi, Konstantinos Makantasis +2
Domain randomisation enhances the transferability of vision models across visually distinct domains with similar content. However, current methods heavily depend on intricate simul…
Predicting Player Engagement in Tom Clancy's The Division 2: A Multimodal Approach via Pixels and Gamepad Actions
Kosmas Pinitas, David Renaudie, Mike Thomsen +4
This paper introduces a large scale multimodal corpus collected for the purpose of analysing and predicting player engagement in commercial-standard games. The corpus is solicited…
Affective Game Computing: A Survey
Georgios N. Yannakakis, David Melhart
This paper surveys the current state of the art in affective computing principles, methods and tools as applied to games. We review this emerging field, namely affective game compu…
Knowing Your Annotator: Rapidly Testing the Reliability of Affect Annotation
Matthew Barthet, Chintan Trivedi, Kosmas Pinitas +4
The laborious and costly nature of affect annotation is a key detrimental factor for obtaining large scale corpora with valid and reliable affect labels. Motivated by the lack of t…
Lode Enhancer: Level Co-creation Through Scaling
Debosmita Bhaumik, Julian Togelius, Georgios N. Yannakakis +1
We explore AI-powered upscaling as a design assistance tool in the context of creating 2D game levels. Deep neural networks are used to upscale artificially downscaled patches of l…