Institute of Information Science, Academia Sinica

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Exact Solutions in the Age of Deep learning

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Exact Solutions in the Age of Deep learning

  • LecturerProf. Ting-Han Wei (University of Alberta, Canada)
    Host: Ti-Rong Wu
  • Time2022-11-03 (Thu.) 14:00 ~ 15:30
  • LocationN106, IIS
Live Stream

meeting link:【webex

code:2514 587 5969

password:yVmFj8PCn33

Abstract
Search is one of the key tools in the artificial intelligence toolbox. Being able to navigate large search spaces intelligently can play a major role in solving difficult problems. A traditional approach combines fast heuristics with efficient search algorithms to produce exact solutions, e.g. Boolean satisfiability problems, game solving, etc.
On the other hand, relatively slower but more accurate machine-learned heuristics have brought about major milestones, the best example of which is the AlphaZero family of algorithms. More specifically, AlphaZero combines Monte Carlo tree search with deep reinforcement learning to achieve superhuman level strength in heuristic play for a wide range of games.
At the University of Alberta, under the supervision of Prof. Martin Müller, we explore many research topics surrounding exact and machine-learned methods. In this talk, I will introduce a number of our projects, sorted into three categories:
1. Integrating exact solution methods with AlphaZero-like architectures
2. Evaluating deep reinforcement learning against exact solutions
3. Heuristic search and learning in imperfect domains