Decoupled Search: A New Form of State-Space Exploration
Álvaro TorralbaAalborg University
Bio: Álvaro Torralba is Associate Professor at the University of Aalborg, Denmark. His research interests are on algorithmic approaches for general problem solving, such as heuristic search, and their application into Automated Planning and optimization. His research has been focused on new methods for efficiently performing search, such as symbolic search with BDDs, decoupled search, or other forms of guidance such as heuristic and dominance analysis functions.
On Clashing Wavefronts in Pareto Search
Sabine StorandtUniversität Konstanz
Bio: Sabine Storandt has been a professor at the University of Konstanz since 2018 and leads the group on Algorithmics. Her research focuses on graph algorithms, algorithm engineering, and discrete optimization.
Programmatic Policies for Game Playing
Levi LelisUniversity of Alberta
Bio: Levi Lelis’ research goal is to develop intelligent systems that are able to augment people through teaching and collaboration. Currently, his group is working on algorithms to generate human-interpretable knowledge, such as programmatic policies for solving sequential decision-making problems. They seek to use machine-generated knowledge to teach humans how to solve problems. For example, these machine-created interpretable policies can be used to compile human-readable manuals for teaching people game strategies. Levi is also interested in investigating the use of interpretable machine-generated knowledge in human-machine collaborative tasks, where algorithms help humans solve problems. Levi is currently an Assistant Professor in the Department of Computing Science at the University of Alberta.
Towards massively parallelized search-based planning in robotics
Maxim LikhachevCarnegie Mellon University
Bio: Maxim Likhachev is a Professor of Robotics at Carnegie Mellon University, directing Search-based Planning Laboratory (SBPL). His group at CMU researches heuristic search, decision-making and planning algorithms, all with applications to the control of robotic systems including unmanned ground and aerial vehicles, mobile manipulation platforms, humanoids, and multi-robot systems. Maxim obtained his Ph.D. in Computer Science from Carnegie Mellon University with a thesis called “Search-based Planning for Large Dynamic Environments.” He has over 150 publications in top journals and conferences on AI and Robotics and numerous paper awards. His work on Anytime D* algorithm, an anytime planning algorithm for dynamic environments, has been awarded the title of Influential 10-year Paper at International Conference on Automated Planning and Scheduling (ICAPS) 2017, the top venue for research on planning and scheduling. Some of the other awards include selection for 2010 DARPA Computer Science Study Panel that recognizes promising faculty in Computer Science and being on a team that won 2007 DARPA Urban Challenge and on a team that won the Gold Edison award in 2013. Maxim founded RobotWits, a company devoted to developing advanced planning and decision-making technologies for self-driving vehicles and recently acquired by Waymo, and co-founded TravelWits, an online travel tech company that brings AI to make travel logistics easier. Finally, Maxim is an executive co-producer of regional Emmy-nominated The Robot Doctor TV series aimed at showing the use of mathematics in Robotics and inspiring high-school students to pursue careers in science and technology.