25 citations · 101 across the 7 of their papers we have counts for
12 papers · 1 filter
Evaluating the Rainbow DQN Agent in Hanabi with Unseen Partners
Rodrigo Canaan, Xianbo Gao, Youjin Chung +3
Hanabi is a cooperative game that challenges exist-ing AI techniques due to its focus on modeling the mental states ofother players to interpret and predict their behavior. While t…
Generating and Adapting to Diverse Ad-Hoc Cooperation Agents in Hanabi
Rodrigo Canaan, Xianbo Gao, Julian Togelius +2
Hanabi is a cooperative game that brings the problem of modeling other players to the forefront. In this game, coordinated groups of players can leverage pre-established convention…
Evaluation of a Recommender System for Assisting Novice Game Designers
Tiago Machado, Daniel Gopstein, Oded Nov +3
Game development is a complex task involving multiple disciplines and technologies. Developers and researchers alike have suggested that AI-driven game design assistants may improv…
Diverse Agents for Ad-Hoc Cooperation in Hanabi
Rodrigo Canaan, Julian Togelius, Andy Nealen +1
In complex scenarios where a model of other actors is necessary to predict and interpret their actions, it is often desirable that the model works well with a wide variety of previ…
Leveling the Playing Field -- Fairness in AI Versus Human Game Benchmarks
Rodrigo Canaan, Christoph Salge, Julian Togelius +1
From the beginning if the history of AI, there has been interest in games as a platform of research. As the field developed, human-level competence in complex games became a target…
Evolving Agents for the Hanabi 2018 CIG Competition
Rodrigo Canaan, Haotian Shen, Ruben Rodriguez Torrado +3
Hanabi is a cooperative card game with hidden information that has won important awards in the industry and received some recent academic attention. A two-track competition of agen…
Towards Game-based Metrics for Computational Co-creativity
Rodrigo Canaan, Stefan Menzel, Julian Togelius +1
We propose the following question: what game-like interactive system would provide a good environment for measuring the impact and success of a co-creative, cooperative agent? Crea…
Generating Levels That Teach Mechanics
Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros +2
The automatic generation of game tutorials is a challenging AI problem. While it is possible to generate annotations and instructions that explain to the player how the game is pla…
AtDelfi: Automatically Designing Legible, Full Instructions For Games
Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros +3
This paper introduces a fully automatic method for generating video game tutorials. The AtDELFI system (AuTomatically DEsigning Legible, Full Instructions for games) was created to…
Talakat: Bullet Hell Generation through Constrained Map-Elites
Ahmed Khalifa, Scott Lee, Andy Nealen +1
We describe a search-based approach to generating new levels for bullet hell games, which are action games characterized by and requiring avoidance of a very large amount of projec…
Procedural Content Generation via Machine Learning (PCGML)
Adam Summerville, Sam Snodgrass, Matthew Guzdial +5
This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content…
PCG-Based Game Design Patterns
Michael Cook, Mirjam Eladhari, Andy Nealen +5
People enjoy encounters with generative software, but rarely are they encouraged to interact with, understand or engage with it. In this paper we define the term 'PCG-based game',…