Dr. Sam Philip Snodgrass

AI Researcher

Affiliation: modl.ai

Email: Sam.PSnodgrass@gmail.com

I am an AI researcher at modl.ai developing designer-facing PCG tools, Personalization methods, and Game Playing agents. My thesis work was on using Markov models for procedural content generation (PCG), and more generally the application of machine learning to PCG (or PCGML). I am continuing to explore PCGML with a particular focus on making PCGML more accessible through domain blending and more autonomous systems.

Journal Articles

Liu, Jialin, Sam Snodgrass, Ahmed Khalifa, Sebastian Risi, Georgios Yannakakis, Julian Togelius. Deep Learning for Procedural Content Generation. Neural Computing and Applications. 2021. [PDF]

Summerville, Adam, Sam Snodgrass, Matthew Guzdial, Christoffer Holmgård, Amy K. Hoover, Aaron Isaksen, Andy Nealen, Julian Togelius. Procedural Content Generation via Machine Learning (PCGML). IEEE Transactions on Games. 2018 . [PDF]

Snodgrass, Sam, and Santiago Ontanón. Learning to Generate Video Game Maps Using Markov Models. IEEE Transactions on Computational Intelligence and AI in Games. 2016. [PDF]


Conference Papers

Sarkar, Anurag, Adam Summerville, Sam Snodgrass, Gerard Bentley, Joseph Osborn. Exploring Level Blending across Platformers via Paths and Affordances. Sixteenth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE). 2020. [PDF]

Snodgrass, Sam, Anurag Sarkar. Multi-Domain Level Generation and Blending with Sketches via Example-Driven BSP and Variational Autoencoders. Proceedings of the Fifteenth International Conference on the Foundations of Digital Games (FDG). 2020. [PDF]

Volz, Vanessa, Niels Justesen, Sam Snodgrass, Sahar Asadi, Sami Purmonen, Christoffer Holmgård, Julian Togelius, Sebastian Risi. Capturing Local and Global Patterns in Procedural Content Generation via Machine Learning. Conference on Games (CoG). 2020. [PDF]

Snodgrass, Sam. Levels from Sketches with Example-Driven Binary Space Partition. Fifteenth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE). 2019. [PDF]

Snodgrass, Sam and Omid Mohaddesi, Jack Hart, Guillermo Romera Rodriguez, Christoffer Holmgard, Casper Harteveld. Like PEAS in PoDS: the Player, Environment, Agents, System Framework for the Personalization of Digital Systems. Proceedings of the Fourteenth International Conference on the Foundations of Digital Games. 2019. [PDF]

Partlan, Nathan, Elin Carstensdottir, Erica Kleinman, Sam Snodgrass, Casper Harteveld, Gillian Smith, Camillia Matuk, Steven C Sutherland, Magy Seif El-Nasr. Evaluation of an Automatically Constructed Graph-based Representation for Interactive Narrative. Proceedings of the Fourteenth International Conference on the Foundations of Digital Games. 2019. [PDF]

Troiano, Giovanni Maria, Sam Snodgrass, Erinc Argimak, Gregorio Robles, Gillian Smith, Michael Cassidy, Eli Tucker-Raymond, Gillian Puttick, Casper Harteveld. Is My Game OK Dr. Scratch?: Exploring Programming and Computational Thinking Development via Metrics in Student-Designed Serious Games for STEM. Proceedings of the Eighteenth ACM International Conference on Interaction Design and Children (IDC). 2019. [PDF]

Partlan, Nathan, Elin Carstensdottir, Sam Snodgrass, Erica Kleinman, Gillian Smith, Casper Harteveld, Magy Seif El-Nasr. Exploratory Automated Analysis of Structural Features of Interactive Narrative. Fourteenth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE). 2018. [PDF]

Ontanón, Santiago, Yi-Ching Lee, Sam Snodgrass, Flaura K Winston, Avelino J Gonzalez. Learning to Predict Driver Behavior from Observation. AAAI Spring Symposium Series. 2017. [PDF]

Snodgrass, Sam, Adam Summerville, Santiago Ontanón. Studying the Effects of Training Data on Machine Learning-based Procedural Content Generation. Thirteenth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE). 2017. [PDF]

Summerville, Adam, Julian R. H. Marino, Sam Snodgrass, Santiago Ontanón, Levi H. S. Lelis. Understanding Mario: An Evaluation of Design Metrics for Platformers. Twelfth International Conference on the Foundations of Digital Games (FDG). 2017. [PDF]

Snodgrass, Sam and Santiago Ontanón. Procedural Level Generation using Multi-layer Level Representations with MdMCs. Computational Intelligence and Games (CIG), 2017 IEEE Conference on. IEEE, 2017. [PDF]

Snodgrass, Sam and Santiago Ontanón. Player Movement Models for Video Game Level Generation. Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI). 2017. [PDF]

Ontañón, Santiago, Yi-Ching Li, Sam Snodgrass, Flaura K. Winston, Avelino J. Gonzalez Learning to Predict Driver Behavior from Observation Proceedings of the AAAI Spring Symposium: Learning from Observation of Humans, Stanford, USA. 2017. [PDF]

Snodgrass, Sam, and Santiago Ontanón. An Approach to Domain Transfer in Procedural Content Generation of Two-Dimensional Videogame Levels. Twelfth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE). 2016. [PDF]

Snodgrass, Sam, and Santiago Ontanón. Controllable Procedural Content Generation via Constrained Multi-Dimensional Markov Chain Sampling. Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI). 2016. [PDF]

Snodgrass, Sam, and Santiago Ontañón. A Hierarchical MdMC Approach to 2D Video Game Map Generation. Eleventh Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE). 2015. [PDF]

Snodgrass, Sam, and Santiago Ontañón. A Hierarchical Approach to Generating Maps Using Markov Chains. Tenth Artificial Intelligence and Interactive Digital Entertainment Conference (AIIDE). 2014. [PDF]

Ontañón, Santiago, Yi-Ching Li, Sam Snodgrass, Dana Bonfiglio, Flaura K. Winston, Catherine McDonald, Avelino J. Gonzalez. Case-Based Prediction of Teen Driver Behavior and Skill. Case-Based Reasoning Research and Development. Springer International Publishing, 2014. 375-389. [PDF]

Snodgrass, Sam, and Santiago Ontañón. Experiments in Map Generation using Markov Chains. Ninth International Conference on the Foundations of Digital Games (FDG). 2014. [PDF]


Workshop Papers/Work in Progress Papers/Technical Reports

Summerville, Adam, Anurag Sarkar, Sam Snodgrass, Joseph Osborn. Extracting Physics from Blended Game Levels. Seventh Experimental AI in Games (EXAG) workshop. 2020. [PDF]

Snodgrass, Sam, Omid Mohaddesi, Casper Harteveld. Towards a Generalized Player Model through the PEAS Framework. Proceedings of the Workshop on User Experience of AI in Games. 2019. [PDF]

Snodgrass, Sam. Towards Automatic Extraction of Tile Types from Level Images. Fifth Experimental AI in Games (EXAG) workshop. 2018. [PDF]

Harteveld, Casper, Sam Snodgrass, Omid Mohaddesi, Jack Hart, Tyler Corwin, Guillermo Romera Rodriguez. The Development of a Methodology for Gamifying Surveys. Proceedings of the 2018 Annual Symposium on Computer-Human Interaction in Play (CHI PLAY) Companion Extended Abstracts. 2018. [PDF]

Snodgrass, Sam, Santiago Ontanón. Leveraging Multi-Layer Level Representations for Puzzle-Platformer Level Generation. Fourth Experimental AI in Games (EXAG) workshop. 2017. [PDF]

Summerville, Adam James, Sam Snodgrass, Santiago Ontanón, Michael Mateas. The VGLC: The Video Game Level Corpus. Proceedings of the 7th Workshop on Procedural Content Generation at 1st Joint International Conference of DiGRA and FDG. 2016. [PDF]

Snodgrass, Sam, Benjamin Goldberg, Ariel Evans, Brandon Packard, Cathy Lu, Jichen Zhu. Extended abstract for Canvas Obscura. Proceedings of the first ACM SIGCHI annual symposium on Computer-Human Interaction in Play (CHI PLAY). ACM, 2014. [PDF]

Snodgrass, Sam, and David W. Aha. System Model Formulation Using Markov Chains. (Technical Note AIC-14-170). Washington, DC: Naval Research Laboratory, Navy Center for Applied Research in AI. 2014.[Technical Report]

Snodgrass, Sam, and Santiago Ontañón. Generating Maps Using Markov Chains. AIIDE Workshop on Artificial Intelligence and Game Aesthetics. 2013. [PDF]


Invited Talks and Tutorials

Snodgrass, Sam. Leveraging Multi-layer Representations for Procedural Level Generation. Asynchronous Research on AI and Games (ASYNC). Remote presentation hosted by Meta-Makers at Falmouth University. 2017.

Snodgrass, Sam and Adam Summerville. Tutorial on Procedural Content Generation via Machine Learning. Computational Intelligence in Games. 2017.


Service and Community Involvement

  • Organizing

    • Artifact Evaluation Chair at AIIDE 2019

    • Co-Organizer of Procedural Content Generation (PCG) Workshop at FDG 2019

    • Co-Organizer of Knowledge Extraction from Games (KEG) at AAAI 2019

  • Reviewing

    • Transactions on Games, 2018. (ToG 2018-2020) [Formerly TCIAIG]

    • Transactions on Computational Intelligence and Artificial Intelligence in Games. (TCIAIG 2017 - 2018)

    • International Joint Conference on Artificial Intelligence. (IJCAI 2019 - 2020)

    • Foundations of Digital Games. (FDG 2015 - 2020)

    • Conference on Games. (CoG 2019 - 2020) [Formerly CIG]

    • Artificial Intelligence in Digital Entertainment. (AIIDE 2018-2019)

    • Computational Intelligence and Games. (CIG 2018)

    • Experimental AI in Games Workshop (EXAG 2020)

    • Procedural Content Generation Workshop. (PCG 2017 - 2018)

    • Knowledge Extraction from Games Workshop. (KEG 2018)

    • Third Computational Creativity and Games Workshop, 2017. (CCGW 2017)

  • Mentoring

    • Master's Thesis of Guillermo Romera Rodriguez at Northeastern University

    • Research Experience for Teachers (REThink)

      • Guided two high school teachers through a Summer-long project on procedural content generation.

    • Mentored 3 high school students visiting Drexel University (on 3 separate occasions) as they worked on projects related to procedural content generation