Dziekan Wydziału serdecznie zaprasza pracowników oraz studentów na
seminarium wydziałowe, które
odbędzie się we wtorek 25 lutego o godz. 12.30 (Instytut Informatyki, sala 119). Prelegentem będzie
dr hab. Henryk Michalewski z Uniwersytetu Warszawskiego, który wygłosi wykład pt.
"Machine learning and theorem proving".
Przed seminarium, o godz. 12.00, Dziekan zaprasza na kawę i ciastko.
Abstract: In my talk I will describe how theorem proving can be phrased as a
machine learning problem and provide experimental results with
regard to various datasets consisting of mathematical problems ranging
from SAT problems to simple arithmetic problems involving addition and
multiplication, to theorem proving inspired by simplifications and
rewritings of SQL queries and finally to general mathematical problems
such as included in
the Mizar Mathematical library.
The talk will cover in
particular the following topics:
- two reinforcement learning algorithms designed for theorem proving;
one of them presented at NeurIPS 2018 in the paper
Reinforcement learning of Theorem Proving
runs Monte-Carlo simulations guided by policy and value functions
gradually updated using previous proof attempts. The other algorithm
is based on curriculum learning and is described in the paper
Towards Finding Longer Proofs,
(project webpage:
www). It complements the
Monte Carlo method in two respects: it may be deployed to solve just
one mathematical problem and overall it is capable to produce longer
proofs.
- a graph network architecture which includes sigmoidal attention
( pdf)
with an empirical study which
shows that this kind of graph representation helps neural guidance of
SAT solving algorithms.
- I will show how rewriting of SQL queries can be phrased as a theorem
proving problem, explain why reinforcement learning is a suitable
framework for optimization of queries and present initial experimental
results obtained with Michael Benedikt and Cezary Kaliszyk.
Bio:
Henryk Michalewski's Masters and PhD theses concerned topology,
mathematical logic and games. In his Habilitation, he turned to the
theory of automata on trees, which plays an important role in
theoretical computer science.
From logic, automata, and the theory of general games, he turned to
the practice of games in the usual human sense, starting from applying
optimization methods to Morpion Solitaire. This was his entry point
into machine learning and led to a series of papers on Atari games and
Deep Reinforcement learning, including
Learning from the memory of Atari 2600,
Hierarchical Reinforcement Learning with Parameters,
Distributed Deep Reinforcement Learning: Learn how to play Atari games in 21 minutes,
a joint
project with Google Brain on Model-Based Reinforcement Learning for
Atari games
(
www)
which
was accepted as a spotlight at ICLR 2020 and a joint project with
Volkswagen on autonomous driving
(
pdf)
which was accepted for ICRA 2020.
Henryk Michalewski is a professor at the University of Warsaw. From
October 2019 he is working as a Staff Visiting Faculty Researcher
at Google.