Vladimir Lifschitz
Encyclopedia
Vladimir Lifschitz is Gottesman Family Centennial Professor in Computer Sciences at the University of Texas at Austin. He received a degree in mathematics from the Steklov Institute of Mathematics
in Russia in 1971 and emigrated to the United States in 1976. Lifschitz's research interests are in the areas of computational logic and knowledge representation. He is a Fellow of the American Association for Artificial Intelligence, the Editor-in-Chief of the ACM Transactions on Computational Logic, and an Editorial Advisor of the journal Theory and Practice of Logic Programming.
He, together with Michael Gelfond, defined stable model semantics
for logic programs, which later became the theoretical foundation for Answer Set Programming
, a new declarative programming paradigm.
Steklov Institute of Mathematics
Steklov Institute of Mathematics or Steklov Mathematical Institute is a research institute based in Moscow, specialized in mathematics, and a part of the Russian Academy of Sciences. It was established April 24, 1934 by the decision of the General Assembly of the Academy of Sciences of the USSR in...
in Russia in 1971 and emigrated to the United States in 1976. Lifschitz's research interests are in the areas of computational logic and knowledge representation. He is a Fellow of the American Association for Artificial Intelligence, the Editor-in-Chief of the ACM Transactions on Computational Logic, and an Editorial Advisor of the journal Theory and Practice of Logic Programming.
He, together with Michael Gelfond, defined stable model semantics
Stable model semantics
The concept of a stable model, or answer set, is used to define a declarative semantics for logic programs with negation as failure. This is one of several standard approaches to the meaning of negation in logic programming, along with program completion and the well-founded semantics...
for logic programs, which later became the theoretical foundation for Answer Set Programming
Answer set programming
Answer set programming is a form of declarative programming oriented towards difficult search problems. It is based on the stable model semantics of logic programming. In ASP, search problems are reduced to computing stable models, and answer set solvers -- programs for generating stable...
, a new declarative programming paradigm.