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Solving decidability problems using automated reasoning techniques

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  • Full or part time
    Dr R Schmidt
  • Application Deadline
    Applications accepted all year round
  • Competition Funded PhD Project (Students Worldwide)
    Competition Funded PhD Project (Students Worldwide)

Project Description

Decidability problems are among the most important and deeply studied problems in computer science, mathematics and logic. Decidability problems involve finding a decision procedure for a problem or proving that no decision procedure exists. Procedures that can determine in a finite number of steps whether a property (expressed as a formula) is true, or not, in a formalisation are decision procedures.

In this project the aim is to use automated reasoning techniques as tools to solve decidability problems related to modal logics, description logics and solvable fragments of first-order logic and applications such as ontology engineering and agent-based systems.

Because we are interested in having actually running systems the aim will be to develop practical, i.e. implementable, decision procedures.

Using techniques from automated reasoning has the advantage that practical decision decision procedures can often be obtained with modest implementation effort. Our interest is, in particular, developing resolution decision procedures. Resolution provides a very powerful theoretical framework for developing decision procedures and many well-developed resolution theorem provers exist which follow this framework and provide platforms for obtaining practical decision procedures.

The project is ideal for someone with a keen interest in computational logic, artificial intelligence, formal methods and automated reasoning.

Funding Notes

Candidates who have been offered a place for PhD study in the School of Computer Science may be considered for funding by the School. Further details on School funding can be found at:


For further details about this project, please see here:

The minimum requirements to get a place in our PhD programme are available from:

How good is research at University of Manchester in Computer Science and Informatics?

FTE Category A staff submitted: 44.86

Research output data provided by the Research Excellence Framework (REF)

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