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!
|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.|
AIJSimple and Efficient Bi-Objective Search Algorithms via Fast Dominance ChecksArtificial Intelligence, 2023
JAIRCommunication-Aware Local Search for Distributed Constraint OptimizationJournal of Artificial Intelligence Research, 2022
JAIRA Logic-Based Explanation Generation Framework for Classical and Hybrid Planning ProblemsJournal of Artificial Intelligence Research, 2022
ICAPSUsing Simple Incentives to Improve Two-Sided Fairness in Ridesharing SystemsIn International Conference on Automated Planning and Scheduling, 2023