143 citations · 546 across the 35 of their papers we have counts for
7 papers · 1 filter
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…
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…
Mutation Models: Learning to Generate Levels by Imitating Evolution
Ahmed Khalifa, Michael Cerny Green, Julian Togelius
Search-based procedural content generation (PCG) is a well-known method for level generation in games. Its key advantage is that it is generic and able to satisfy functional constr…
Persona-driven Dominant/Submissive Map (PDSM) Generation for Tutorials
Michael Cerny Green, Ahmed Khalifa, M Charity +1
In this paper, we present a method for automated persona-driven video game tutorial level generation. Tutorial levels are scenarios in which the player can explore and discover dif…
Predicting Personas Using Mechanic Frequencies and Game State Traces
Michael Cerny Green, Ahmed Khalifa, M Charity +2
We investigate how to efficiently predict play personas based on playtraces. Play personas can be computed by calculating the action agreement ratio between a player and a generati…
Baba is Y'all 2.0: Design and Investigation of a Collaborative Mixed-Initiative System
M Charity, Isha Dave, Ahmed Khalifa +1
This paper describes a new version of the mixed-initiative collaborative level designing system: Baba is Y'all, as well as the results of a user study on the system. Baba is Y'all…