143 citations · 781 across the 60 of their papers we have counts for
13 papers · 1 filter
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…
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…
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…
The Invariant Ground Truth of Affect
Konstantinos Makantasis, Kosmas Pinitas, Antonios Liapis +1
Affective computing strives to unveil the unknown relationship between affect elicitation, manifestation of affect and affect annotations. The ground truth of affect, however, is p…
Generative Personas That Behave and Experience Like Humans
Matthew Barthet, Ahmed Khalifa, Antonios Liapis +1
Using artificial intelligence (AI) to automatically test a game remains a critical challenge for the development of richer and more complex game worlds and for the advancement of A…
Seeding Diversity into AI Art
Marvin Zammit, Antonios Liapis, Georgios N. Yannakakis
This paper argues that generative art driven by conformance to a visual and/or semantic corpus lacks the necessary criteria to be considered creative. Among several issues identifi…
Experience-Driven PCG via Reinforcement Learning: A Super Mario Bros Study
Tianye Shu, Jialin Liu, Georgios N. Yannakakis
We introduce a procedural content generation (PCG) framework at the intersections of experience-driven PCG and PCG via reinforcement learning, named ED(PCG)RL, EDRL in short. EDRL…
Transforming Exploratory Creativity with DeLeNoX
Antonios Liapis, Hector P. Martinez, Julian Togelius +1
We introduce DeLeNoX (Deep Learning Novelty Explorer), a system that autonomously creates artifacts in constrained spaces according to its own evolving interestingness criterion. D…
Deep Learning for Procedural Content Generation
Jialin Liu, Sam Snodgrass, Ahmed Khalifa +3
Procedural content generation in video games has a long history. Existing procedural content generation methods, such as search-based, solver-based, rule-based and grammar-based me…
I Feel I Feel You: A Theory of Mind Experiment in Games
David Melhart, Georgios N. Yannakakis, Antonios Liapis
In this study into the player's emotional theory of mind of gameplaying agents, we investigate how an agent's behaviour and the player's own performance and emotions shape the reco…