publications

\* denotes equal contribution

2024

  1. TELO
    Covariance Matrix Adaptation MAP-Annealing: Theory and Experiments
    Shihan Zhao, Bryon Tjanaka, Matthew C. Fontaine, and Stefanos Nikolaidis
    ACM Transactions on Evolutionary Learning and Optimization, 2024
  2. AAAI
    Quality-Diversity Generative Sampling for Learning with Synthetic Data
    Allen Chang, Matthew C. Fontaine, Serena Booth, Maja J Matarić, and Stefanos Nikolaidis
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2024
    Acceptance rate: 23.75%
  3. GECCO
    Generating Diverse Critics for Conditioned Policy Distillation
    Ryan Boldi, Matthew C. Fontaine, Sumeet Batra, Gaurav Sukhatme, and Stefanos Nikolaidis
    In Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024
  4. ICLR
    Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
    Sumeet Batra, Bryon Tjanaka, Matthew C. Fontaine, Aleksei Petrenko, Stefanos Nikolaidis, and Gaurav S. Sukhatme
    In The Twelfth International Conference on Learning Representations, 2024
    Acceptance rate: 6.2%
    Spotlight
  5. GECCO
    Density Descent for Diversity Optimization
    David H Lee, Anishalakshmi Palaparthi, Matthew C. Fontaine, Bryon Tjanaka, and Stefanos Nikolaidis
    In Proceedings of the Genetic and Evolutionary Computation Conference, 2024
    Acceptance rate: 36%

2023

  1. NeurIPS
    Arbitrarily Scalable Environment Generators via Neural Cellular Automata
    Yulun Zhang, Matthew C. Fontaine, Varun Bhatt, Stefanos Nikolaidis, and Jiaoyang Li
    Advances in Neural Information Processing Systems, 2023
    Acceptance rate: 26.1%
  2. IJCAI
    Multi-Robot Coordination and Layout Design for Automated Warehousing
    Yulun Zhang, Matthew C. Fontaine, Varun Bhatt, Stefanos Nikolaidis, and Jiaoyang Li
    In Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, IJCAI-23, Aug 2023
    Acceptance rate: 14.1%
    DOI
  3. CoRL
    Surrogate Assisted Generation of Human-Robot Interaction Scenarios
    Varun Bhatt, Heramb Nemlekar, Matthew C. Fontaine, Bryon Tjanaka, Hejia Zhang, Ya-Chuan Hsu, and Stefanos Nikolaidis
    Conference on Robot Learning (CoRL), Aug 2023
    Acceptance rate: 6.63%
    Oral
  4. RA-L
    Training diverse high-dimensional controllers by scaling covariance matrix adaptation map-annealing
    Bryon Tjanaka, Matthew C. Fontaine, David H Lee, Aniruddha Kalkar, and Stefanos Nikolaidis
    IEEE Robotics and Automation Letters, Aug 2023
  5. GECCO
    Covariance Matrix Adaptation MAP-Annealing
    Matthew C. Fontaine, and Stefanos Nikolaidis
    In Proceedings of the 2023 Genetic and Evolutionary Computation Conference (GECCO), Aug 2023
    Best Paper
  6. GECCO
    pyribs: A bare-bones Python library for quality diversity optimization
    Bryon Tjanaka, Matthew C. Fontaine, David H Lee, Yulun Zhang, Nivedit Reddy Balam, Nathaniel Dennler, Sujay S Garlanka, Nikitas Dimitri Klapsis, and Stefanos Nikolaidis
    In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO), Aug 2023
    Acceptance rate: 35.1%
  7. RSS
    Quality Diversity Scenario Generation for Evaluating Human-Robot Interaction
    Matthew C. Fontaine
    RSS Pioneers, Aug 2023

2022

  1. NeurIPS
    Deep Surrogate Assisted Generation of Environments
    Varun Bhatt, Bryon Tjanaka, Matthew C. Fontaine, and Stefanos Nikolaidis
    In Advances in Neural Information Processing Systems, Aug 2022
    Acceptance rate: 25.6%
  2. ToH
    Preference-Driven Texture Modeling Through Interactive Generation and Search
    Shihan Lu, Mianlun Zheng, Matthew C. Fontaine, Stefanos Nikolaidis, and Heather Marie Culbertson
    IEEE Transactions on Haptics, Aug 2022
  3. GECCO
    Approximating Gradients for Differentiable Quality Diversity in Reinforcement Learning
    Bryon Tjanaka, Matthew C. Fontaine, Julian Togelius, and Stefanos Nikolaidis
    In Proceedings of the Genetic and Evolutionary Computation Conference, Boston, Massachusetts, Aug 2022
    Acceptance rate: 37%
    DOI
  4. GECCO
    Deep surrogate assisted MAP-elites for automated hearthstone deckbuilding
    Yulun Zhang, Matthew C. Fontaine, Amy K. Hoover, and Stefanos Nikolaidis
    In Proceedings of the Genetic and Evolutionary Computation Conference, Aug 2022
    Acceptance rate: 37%
  5. AAAI
    Towards Automating the Generation of Human-Robot Interaction Scenarios
    Matthew C. Fontaine
    AAAI Doctoral Consortium, Aug 2022
  6. GECCO
    Illuminating diverse neural cellular automata for level generation
    Sam Earle, Justin Snider, Matthew C. Fontaine, Stefanos Nikolaidis, and Julian Togelius
    In Proceedings of the Genetic and Evolutionary Computation Conference, Aug 2022
    Acceptance rate: 37%
  7. SIGGRAPH
    Generating Diverse Indoor Furniture Arrangements
    Ya-Chuan Hsu, Matthew C. Fontaine, Sam Earle, Maria Edwards, Julian Togelius, and Stefanos Nikolaidis
    In ACM SIGGRAPH 2022 Posters, Aug 2022

2021

  1. NeurIPS
    Differentiable Quality Diversity
    Matthew C. Fontaine, and Stefanos Nikolaidis
    Advances in Neural Information Processing Systems, Aug 2021
    Acceptance rate: 0.5%
    Oral
  2. THRI
    Evaluating Human-Robot Interaction Algorithms in Shared Autonomy via Quality Diversity Scenario Generation
    Matthew C. Fontaine, and Stefanos Nikolaidis
    ACM Transactions on Human-Robot Interaction (THRI), Aug 2021
  3. RSS
    On the Importance of Environments in Human-Robot Coordination
    Matthew C. Fontaine*, Ya-Chuan Hsu*, Yulun Zhang*, Bryon Tjanaka, and Stefanos Nikolaidis
    In Robotics Science and Systems (RSS), Aug 2021
    Acceptance rate: 27%
  4. RSS
    A Quality Diversity Approach to Automatically Generating Human-Robot Interaction Scenarios in Shared Autonomy
    Matthew C. Fontaine, and Stefanos Nikolaidis
    In Robotics Science and Systems (RSS), Aug 2021
    Acceptance rate: 27%
  5. AAAI
    Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Network
    Matthew C. Fontaine, Ruilin Liu, Ahmed Khalifa, Jignesh Modi, Julian Togelius, Amy K. Hoover, and Stefanos Nikolaidis
    In 35th AAAI Conference on Artificial Intelligence (AAAI), Aug 2021
    Acceptance rate: 21%

2020

  1. AIIDE
    Video Game Level Repair via Mixed Integer Linear Programming
    Hejia Zhang*, Matthew C. Fontaine*, Amy K. Hoover, Julian Togelius, Bistra Dilkina, and Stefanos Nikolaidis
    In Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE), Aug 2020
    Acceptance rate: 25%
    Oral
  2. GECCO
    Covariance Matrix Adaptation for the Rapid Illumination of Behavior Space
    Matthew C. Fontaine, Julian Togelius, Stefanos Nikolaidis, and Amy K. Hoover
    In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO), Aug 2020
    Acceptance rate: 36%

2019

  1. CoG
    Evolving the hearthstone meta
    Fernando Mesentier Silva, Rodrigo Canaan, Scott Lee, Matthew C. Fontaine, Julian Togelius, and Amy K. Hoover
    In 2019 IEEE Conference on Games (CoG), Aug 2019
    Acceptance rate: 40%
  2. GECCO
    Mapping hearthstone deck spaces through map-elites with sliding boundaries
    Matthew C. Fontaine, Scott Lee, Lisa B. Soros, Fernando Mesentier Silva, Julian Togelius, and Amy K. Hoover
    In Proceedings of The Genetic and Evolutionary Computation Conference, Aug 2019
    Acceptance rate: 35%

2018

  1. Tidal Flow: A Fast and Teachable Maximum Flow Algorithm
    Matthew C. Fontaine
    In Olympiads in Informatics, Aug 2018

2011

  1. User Interface and Information Management of Scenarios
    Robert Louden, Matthew C. Fontaine, Glenn A. Martin, Jason Daly, and Sae Schatz
    In Human Interface and the Management of Information. Interacting with Information, Aug 2011
  2. Technological and Usability-Based Aspects of Distributed After Action Review in a Game-Based Training Setting
    Matthew C. Fontaine, Glenn A. Martin, Jason Daly, and Casey Thurston
    In Engineering Psychology and Cognitive Ergonomics, Aug 2011