The Yeoh’s Optimization and Decision Analytics (YODA) Lab at Washington University in St. Louis uses artificial intelligence based techniques to develop intelligent agent-based systems. Historically, the group has used methods based on decision theory, constraint programming, and heuristic search for intelligent single- and multi-agent systems.

More recently, the group has focused on interdisciplinary approaches to enable human-AI collaboration through human-aware decision-making algorithms. Please visit our research page to find more information on our current research projects!

recent news

Jul 2023: ECAI papers on explainable scheduling and personalized explanations and accepted.
Jul 2023: Received an NSF training grant for AI and environmental social science! Read more about it in this WashU news article.
May 2023: William Yeoh served as a program co-chair of AAMAS 2023.
Apr 2023: IJCAI paper on multi-objective search accepted.
Mar 2023: Received an NSF grant to work on fair and explainable scheduling! Read more about it in this WashU news article.

selected publications

  1. AIJ
    Simple and Efficient Bi-Objective Search Algorithms via Fast Dominance Checks
    Carlos HernándezWilliam YeohJorge A. Baier, Han Zhang, Luis Suazo, Sven Koenig, and Oren Salzman
    Artificial Intelligence, 2023
  2. JAIR
    Communication-Aware Local Search for Distributed Constraint Optimization
    Ben Rachmut, Roie Zivan, and William Yeoh
    Journal of Artificial Intelligence Research, 2022
  3. JAIR
    A Logic-Based Explanation Generation Framework for Classical and Hybrid Planning Problems
    Stylianos Loukas VasileiouWilliam YeohTran Cao SonAshwin Kumar, Michael Cashmore, and Daniele Magazzeni
    Journal of Artificial Intelligence Research, 2022
  4. ICAPS
    Using Simple Incentives to Improve Two-Sided Fairness in Ridesharing Systems
    In International Conference on Automated Planning and Scheduling, 2023