143 citations · 781 across the 60 of their papers we have counts for
11 papers · 1 filter
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…
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…
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…
Open-Ended Evolution for Minecraft Building Generation
Matthew Barthet, Antonios Liapis, Georgios N. Yannakakis
This paper proposes a procedural content generator which evolves Minecraft buildings according to an open-ended and intrinsic definition of novelty. To realize this goal we evaluat…
Play with Emotion: Affect-Driven Reinforcement Learning
Matthew Barthet, Ahmed Khalifa, Antonios Liapis +1
This paper introduces a paradigm shift by viewing the task of affect modeling as a reinforcement learning (RL) process. According to the proposed paradigm, RL agents learn a policy…
Revisiting lp-constrained Softmax Loss: A Comprehensive Study
Chintan Trivedi, Konstantinos Makantasis, Antonios Liapis +1
Normalization is a vital process for any machine learning task as it controls the properties of data and affects model performance at large. The impact of particular forms of norma…
Go-Blend behavior and affect
Matthew Barthet, Antonios Liapis, Georgios N. Yannakakis
This paper proposes a paradigm shift for affective computing by viewing the affect modeling task as a reinforcement learning process. According to our proposed framework the contex…
Keiki: Towards Realistic Danmaku Generation via Sequential GANs
Ziqi Wang, Jialin Liu, Georgios N. Yannakakis
Search-based procedural content generation methods have recently been introduced for the autonomous creation of bullet hell games. Search-based methods, however, can hardly model p…
Pairing Character Classes in a Deathmatch Shooter Game via a Deep-Learning Surrogate Model
Daniel Karavolos, Antonios Liapis, Georgios N. Yannakakis
This paper introduces a surrogate model of gameplay that learns the mapping between different game facets, and applies it to a generative system which designs new content in one of…
Your Gameplay Says It All: Modelling Motivation in Tom Clancy's The Division
David Melhart, Ahmad Azadvar, Alessandro Canossa +2
Is it possible to predict the motivation of players just by observing their gameplay data? Even if so, how should we measure motivation in the first place? To address the above que…
Active Player Modelling
Julian Togelius, Noor Shaker, Georgios N. Yannakakis
We argue for the use of active learning methods for player modelling. In active learning, the learning algorithm chooses where to sample the search space so as to optimise learning…