536 citations · 2k across the 52 of their papers we have counts for
28 papers · 1 filter
A Controllable Co-Creative Agent for Game System Design
Rohan Agarwal, Zhiyu Lin, Mark Riedl
Many advancements have been made in procedural content generation for games, and with mixed-initiative co-creativity, have the potential for great benefits to human designers. Howe…
Detecting and Adapting to Novelty in Games
Xiangyu Peng, Jonathan C. Balloch, Mark O. Riedl
Open-world novelty occurs when the rules of an environment can change abruptly, such as when a game player encounters "house rules". To address open-world novelty, game playing age…
Situated Language Learning via Interactive Narratives
Prithviraj Ammanabrolu, Mark O. Riedl
This paper provides a roadmap that explores the question of how to imbue learning agents with the ability to understand and generate contextually relevant natural language in servi…
Playing Text-Based Games with Common Sense
Sahith Dambekodi, Spencer Frazier, Prithviraj Ammanabrolu +1
Text based games are simulations in which an agent interacts with the world purely through natural language. They typically consist of a number of puzzles interspersed with interac…
How to Avoid Being Eaten by a Grue: Structured Exploration Strategies for Textual Worlds
Prithviraj Ammanabrolu, Ethan Tien, Matthew Hausknecht +1
Text-based games are long puzzles or quests, characterized by a sequence of sparse and potentially deceptive rewards. They provide an ideal platform to develop agents that perceive…
Conceptual Game Expansion
Matthew Guzdial, Mark Riedl
Automated game design is the problem of automatically producing games through computational processes. Traditionally, these methods have relied on the authoring of search spaces by…
Bringing Stories Alive: Generating Interactive Fiction Worlds
Prithviraj Ammanabrolu, Wesley Cheung, Dan Tu +2
World building forms the foundation of any task that requires narrative intelligence. In this work, we focus on procedurally generating interactive fiction worlds---text-based worl…
Learning Norms from Stories: A Prior for Value Aligned Agents
Spencer Frazier, Md Sultan Al Nahian, Mark Riedl +1
Value alignment is a property of an intelligent agent indicating that it can only pursue goals and activities that are beneficial to humans. Traditional approaches to value alignme…
Integrating Automated Play in Level Co-Creation
Andrew Hoyt, Matthew Guzdial, Yalini Kumar +2
In level co-creation an AI and human work together to create a video game level. One open challenge in level co-creation is how to empower human users to ensure particular qualitie…
Monte-Carlo Tree Search for Simulation-based Strategy Analysis
Alexander Zook, Brent Harrison, Mark O. Riedl
Games are often designed to shape player behavior in a desired way; however, it can be unclear how design decisions affect the space of behaviors in a game. Designers usually explo…
Automatic Game Design via Mechanic Generation
Alexander Zook, Mark O. Riedl
Game designs often center on the game mechanics---rules governing the logical evolution of the game. We seek to develop an intelligent system that generates computer games. As firs…
Automatic Playtesting for Game Parameter Tuning via Active Learning
Alexander Zook, Eric Fruchter, Mark O. Riedl
Game designers use human playtesting to gather feedback about game design elements when iteratively improving a game. Playtesting, however, is expensive: human testers must be recr…
Human-Centered Artificial Intelligence and Machine Learning
Mark O. Riedl
Humans are increasingly coming into contact with artificial intelligence and machine learning systems. Human-centered artificial intelligence is a perspective on AI and ML that alg…
Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptions
Upol Ehsan, Pradyumna Tambwekar, Larry Chan +2
Automated rationale generation is an approach for real-time explanation generation whereby a computational model learns to translate an autonomous agent's internal state and action…
Towards Automated Let's Play Commentary
Matthew Guzdial, Shukan Shah, Mark Riedl
We introduce the problem of generating Let's Play-style commentary of gameplay video via machine learning. We propose an analysis of Let's Play commentary and a framework for build…
Co-Creative Level Design via Machine Learning
Matthew Guzdial, Nicholas Liao, Mark Riedl
Procedural Level Generation via Machine Learning (PLGML), the study of generating game levels with machine learning, has received a large amount of recent academic attention. For c…
Explainable PCGML via Game Design Patterns
Matthew Guzdial, Joshua Reno, Jonathan Chen +2
Procedural content generation via Machine Learning (PCGML) is the umbrella term for approaches that generate content for games via machine learning. One of the benefits of PCGML is…
Automated Game Design via Conceptual Expansion
Matthew Guzdial, Mark Riedl
Automated game design has remained a key challenge within the field of Game AI. In this paper, we introduce a method for recombining existing games to create new games through a pr…
Creative Invention Benchmark
Matthew Guzdial, Nicholas Liao, Vishwa Shah +1
In this paper we present the Creative Invention Benchmark (CrIB), a 2000-problem benchmark for evaluating a particular facet of computational creativity. Specifically, we address c…
Explore, Exploit or Listen: Combining Human Feedback and Policy Model to Speed up Deep Reinforcement Learning in 3D Worlds
Zhiyu Lin, Brent Harrison, Aaron Keech +1
We describe a method to use discrete human feedback to enhance the performance of deep learning agents in virtual three-dimensional environments by extending deep-reinforcement lea…
Guiding Reinforcement Learning Exploration Using Natural Language
Brent Harrison, Upol Ehsan, Mark O. Riedl
In this work we present a technique to use natural language to help reinforcement learning generalize to unseen environments. This technique uses neural machine translation, specif…
Enter the Matrix: Safely Interruptible Autonomous Systems via Virtualization
Mark O. Riedl, Brent Harrison
Autonomous systems that operate around humans will likely always rely on kill switches that stop their execution and allow them to be remote-controlled for the safety of humans or…
Rationalization: A Neural Machine Translation Approach to Generating Natural Language Explanations
Upol Ehsan, Brent Harrison, Larry Chan +1
We introduce AI rationalization, an approach for generating explanations of autonomous system behavior as if a human had performed the behavior. We describe a rationalization techn…
Learning to Blend Computer Game Levels
Matthew Guzdial, Mark Riedl
We present an approach to generate novel computer game levels that blend different game concepts in an unsupervised fashion. Our primary contribution is an analogical reasoning pro…