EIT Digital
Automated Reasoning: satisfiability
EIT Digital

Automated Reasoning: satisfiability

Taught in English

Some content may not be translated

4,447 already enrolled


Gain insight into a topic and learn the fundamentals

Hans Zantema

Instructor: Hans Zantema


(41 reviews)

Intermediate level
Some related experience required
25 hours to complete
3 weeks at 8 hours a week
Flexible schedule
Learn at your own pace

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There are 4 modules in this course

This module introduces SAT (satisfiability) and SMT (SAT modulo theories) from scratch, and gives a number of examples of how to apply SAT.

What's included

6 videos2 readings3 quizzes

This module shows a number of applications of satisfiability modulo the theory of linear inequalities (SMT)

What's included

4 videos2 readings7 quizzes

This module describes how a rule called Resolution serves to determine whether a propositional formula in conjunctive normal form (CNF) is unsatisfiable. It is shown how an approach called DPLL does the same job, and how it is related to resolution. Finally, it is shown how current SAT solvers essentially implement and optimize DPLL.

What's included

6 videos5 quizzes

This module consists of two parts. The first part is about transforming arbitrary propositional formulas to CNF, leading to the Tseitin transformation doing this job such that the size of the transformed formula is linear in the size of the original formula. The second part is about extending SAT to SMT, in particular to dealing with linear inequalities. It is shown how the Simplex method for linear optimization serves for this job; the Simplex method itself is explained in detail.

What's included

6 videos4 quizzes


Instructor ratings
4.6 (15 ratings)
Hans Zantema
EIT Digital
2 Courses5,925 learners

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EIT Digital

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