Speaker
Prof.
Bart Selman
(Cornell University)
Description
In recent years, we have seen tremendous progress in
inference technologies. For example, in the area of Boolean
satisfiability (SAT) and Mixed Integer Programming (MIP)
solvers now enable us to tackle significant practical problem
instances from applications in hardware and software
verification, planning, and scheduling. Key to this success is
the ability to strike the right balance between the
expressiveness of the underlying representation formalism
and the efficiency of the solvers. The next challenge is to
extend the reach of these solvers to more complex tasks
that lie beyond NP.
I will discuss our work on sampling, counting, probabilistic reasoning, and adversarial reasoning. In particular, I will discuss a sampling technique based on the so-called flat histogram method from statistical physics. The technique allows for fast probabilistic inference and learning in Markov Logic networks and other graphical models. In the area of adversarial reasoning, the UCT method, based on clever sampling strategies first developed for use in multi-armed bandit scenarios, provides a compelling alternative to traditional minimax search. The method has led to an exciting advance in the strength of GO programs. I'll discuss insights into the surprising effectiveness of the UCT technique.
I will discuss our work on sampling, counting, probabilistic reasoning, and adversarial reasoning. In particular, I will discuss a sampling technique based on the so-called flat histogram method from statistical physics. The technique allows for fast probabilistic inference and learning in Markov Logic networks and other graphical models. In the area of adversarial reasoning, the UCT method, based on clever sampling strategies first developed for use in multi-armed bandit scenarios, provides a compelling alternative to traditional minimax search. The method has led to an exciting advance in the strength of GO programs. I'll discuss insights into the surprising effectiveness of the UCT technique.
Primary author
Prof.
Bart Selman
(Cornell University)
