Schedule
Room – Meeting Room 1&2
| Time | Event |
|---|---|
| 9:00 - 9:15 | Welcome and Opening Remarks |
| 9:15 - 10:00 | Invited Talk from Marcus Hutter |
| 10:00 - 10:30 | AM Break |
| 10:30 - 12:00 | Student Presentation |
| 12:00 - 1:30 | Lunch Break |
| 1:30 - 2:15 | Invited Talk #2 |
| 2:15 - 3:00 | Student Presentation |
| 3:00 - 3:30 | Break |
| 3:30 - 4:15 | Student Presentation |
| 4:15 - 5:30 | Poster Session |
| 6:00- 22:00 | Dinner with Mentors |
Student Presentation Schedule
| Time | Presenter |
|---|---|
| 10:30–10:45 | David Adams |
| 10:45–11:00 | Travis Rivera Petit |
| 11:00–11:15 | Israel Puerta-Merino |
| 11:15–11:30 | Nader Karimi Bavandpour |
| 11:30–11:45 | Paul Zaidins |
| 11:45–12:00 | David H. Chan |
| 2:15–2:30 | Maurice Dekker |
| 2:30–2:45 | Mohammad Yousefi |
| 2:45–3:00 | Daniel Lutalo |
| 3:30–3:45 | Yifan Zhang |
| 3:45–4:00 | Anil B Murthy |
| 4:00–4:15 | Jiajia Song |
Keynote Talks
Title: Universal Algorithmic Intelligence Speaker: Dr. Marcus Hutter
Abstract: There is great interest in understanding and constructing generally intelligent systems approaching and ultimately exceeding human intelligence. Universal AI is such a mathematical theory of machine super-intelligence. More precisely, AIXI is an elegant parameter-free theory of an optimal reinforcement learning agent embedded in an arbitrary unknown environment that possesses essentially all aspects of rational intelligence. The theory reduces all conceptual AI problems to pure computational questions. After a brief discussion of its philosophical, mathematical, and computational ingredients, I will give a formal definition and measure of intelligence, which is maximized by AIXI. AIXI can be viewed as the most powerful Bayes-optimal sequential decision maker, for which I will present general optimality results. This also motivates some variations such as knowledge-seeking and optimistic agents, and feature reinforcement learning. Finally I present some recent approximations, implementations, and applications of this modern top-down approach to AI.
Mini biography: Marcus Hutter is Senior Staff Researcher at DeepMind and Professor in the RSCS at the Australian National University. He received his PhD and BSc in physics from the LMU in Munich and a Habilitation, MSc, and BSc in informatics from the TU Munich. Since 2000, his research at IDSIA and ANU and DeepMind has centered around the information-theoretic foundations of inductive reasoning and reinforcement learning, which has resulted in 200+ publications and several awards. His books on “Universal Artificial Intelligence” develop the first sound and complete theory of super-intelligent machines (ASI). He also runs the Human Knowledge Compression Contest (500'000€ H-prize). See http://www.hutter1.net/ for further information.
Title: Learning Interpretable Models for Autonomous Assessment of Taskable AI Systems Speaker: Dr. Pulkit Verma
Abstract: Taskable AI systems are increasingly expected to operate in diverse, user-specific environments and perform tasks tailored to individual needs, all while improving over time. A critical challenge is determining whether these AI systems can safely and effectively fulfill the specific tasks users have in mind. In this talk, I will present my work on addressing this challenge, including methods for conducting independent, post-deployment differential assessments of AI systems. I will discuss the necessary requirements these systems must meet to enable such assessments. A key aspect of my approach involves a personalized AI assessment module that allows the AI to execute instruction sequences in simulators and respond to user queries about these executions. Finally, I will share our findings demonstrating that even a basic query-response interface can efficiently produce a user-interpretable model of an AI system’s capabilities.
Doctoral Consortium and Launchpad Dinner
Join us for an evening of networking and celebration!
Venue: The Builder’s Arms Hotel
Address: 211 Gertrude Street, Fitzroy VIC 3065
Schedule:
- 6:00 PM - Guests arrive – drinks and canapé service commence
- 10:00 PM - Event concludes
Walking distance: Approximately 30 minutes from The University of Melbourne.
Useful Resources
Here are some helpful links that the ICAPS DC 2022 Organizers compiled
Invited talk by Subbarao (Rao) Kambhampati from ICAPS DC 2020 on Planning in the Age of Deep Learning.
Invited talk by Subbarao (Rao) Kambhampati from IJCAI DC 2013 on How to Write Good Papers and How to Give Good Talks.
Some additional helpful resources shared with us by Dr. Marcus Hutter:
LaTeX Tips & Template & Writing Advice (33 pages accumulated over 25 years of supervising graduate students)