Dear all, Our next AI seminar is scheduled to be on May 10th (Friday), 2-3 PM. Seminar Location: BEXL 320 Student meeting: 3-3:30 pm, KEC 2057 (sign up here<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdocs.google.com%2Fspreadsheets%2Fd%2F1B7jr4V8FHXTCq9EU_rHxd6UIeLL1c5gLFxDycdYGGds%2Fedit%3Fusp%3Dsharing&data=05%7C02%7Cai%40engr.orst.edu%7C052c6cb13b534d4dba6a08dc6f4661f7%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638507595306284362%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=lgdFCp2M0jSXNeAiV%2FN7EqskPymhqX7yA7NNhCsFxAk%3D&reserved=0>) Zoom link: https://oregonstate.zoom.us/j/91611213801?pwd=Wm9JSkN1eW84RUpiS2JEd0E5TEVkdz09<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonstate.zoom.us%2Fj%2F91611213801%3Fpwd%3DWm9JSkN1eW84RUpiS2JEd0E5TEVkdz09&data=05%7C02%7Cai%40engr.orst.edu%7C052c6cb13b534d4dba6a08dc6f4661f7%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638507595306284362%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=7sompGDvA6ZqmML9oeEzemZdSmla4jORNDqY%2FCQ0LLg%3D&reserved=0> When Sparse Data is All You Have: Learning World Models for Generalizable Planning and RL with a View Towards AI Assessment Siddharth Srivastava Associate Professor of Computer Science School of Computing and Augmented Intelligence Arizona State University Abstract: Can we build autonomous agents that learn generalizable knowledge and reliably solve previously unseen problems? In this talk I will present some of my group's recent research on neuro-symbolic learning for sequential decision-making problems that feature long-horizons, sparse rewards and vast differences between training and testing problems. I will discuss methods for learning and using abstractions to learn world models that can be easily transferred to new problem instances, often overshadowing the complexity of training instances. We will see how these methods can be used to invent symbolic vocabularies and learn logic-based world-models for robot task and motion planning without any human annotation or hand-written logic; how learning simple abstractions during Q-learning can vastly improve the performance of RL agents; and finally, how abstractions can help address the emerging problem of AI assessment. Speaker Bio: Siddharth Srivastava is an Associate Professor of Computer Science in the School of Computing and Augmented Intelligence at Arizona State University. He received his Ph.D. in Computer Science at the University of Massachusetts, Amherst, and did his postdoctoral research at UC Berkeley. His research focuses on safe and reliable taskable AI systems and AI assessment. He is a recipient of the NSF CAREER award, a Best Paper award at the International Conference on Automated Planning and Scheduling (ICAPS), an Outstanding Dissertation award at UMass Amherst, and a Best Final Year Thesis Award at IIT Kanpur. He served as conference Co-Chair for ICAPS 2019 and currently serves as an Associate Editor for the Journal of AI Research. Please watch this space for future AI Seminars : https://engineering.oregonstate.edu/EECS/research/AI<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineering.oregonstate.edu%2FEECS%2Fresearch%2FAI&data=05%7C02%7Cai%40engr.orst.edu%7C052c6cb13b534d4dba6a08dc6f4661f7%7Cce6d05e13c5e4d6287a84c4a2713c113%7C0%7C0%7C638507595306284362%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C0%7C%7C%7C&sdata=D0cnotexgI%2BNv%2Bi1CtMapC1egohXrvJOViaCP9Ajkps%3D&reserved=0> Rajesh Mangannavar, Graduate Student Oregon State University ---- AI Seminar Important Reminders: -> For graduate students in the AI program, attendance is strongly encouraged