125 citations · 485 across the 34 of their papers we have counts for
6 papers · 1 filter
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…
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…