Caros,

No dia 15 de maio, segunda-feira, as 14:30h no auditório Padre Anchieta no
prédio Cardeal Leme da PUC-Rio teremos apalestra do Projeto. Moshe  Vardi.

Dentre os diversos prêmios que o Prof. Moshe Vardi obteve estão o ACM
SIGACT Goedel Prize, ACM SIGMOD Codd Award, IBM Outstanding Innovation
Awards e Blaise Pascal Medal.
Mais detalhes sobre sua contribuição para a área de Ciência de Computação
consulte http://www.cs.rice.edu/~vardi/.

Atualmente o Prof. Vardi está na Univesridade de Rice e é editor da
Communications of the ACM.

Sua pesquisa é bastante extensa com trabalhos ligando lógica e computação.

Segue abaixo o título e resumo da palestra, que visa a uma audiência bem
ampla de pessoas ligadas a área de Ciência de Computação, Lógica e
Matemática.


Title and Abstract :

The Automated-Reasoning Revolution: From Theory to Practice and Back

Moshe Y. Vardi
Rice University

For the past 40 years, computer scientists generally believed that
NP-complete problems are intractable. In particular, Boolean
satisfiability (SAT), as a paradigmatic automated-reasoning problem, has
been considered to be intractable. Over the past 20 years, however, there
has been a quiet, but dramatic revolution and very large SAT instances are
now being solved routinely as part of software and hardware design.
In this talk, I will review this amazing development and show how automated
reasoning is now an industrial reality.

I will then describe how we can leverage SAT solving to accomplish other
automated-reasoning tasks. Counting the number of satisfying truth
assignments of a given Boolean formula or sampling such assignments
uniformly at random are fundamental computational problems in computer
science with applications in software testing, software synthesis, machine
learning, personalized learning, and more. While the theory of these
problems has been thoroughly investigated since the 1980s, approximation
algorithms developed by theoreticians do not scale up to industrial-sized
instances. Algorithms used by the industry offer better scalability but
give up certain correctness guarantees to achieve scalability. We describe
a novel approach, based on universal hashing and Satisfiability Modulo
Theory, that scales to formulas with hundreds of thousands of variables
without giving up correctness guarantees.

Abraços,

Bruno.

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