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constraint-programming's Introduction

Constraint Logic Programming

You can see a list of the materials provided in each lecture here.

Objectives

This course addresses the Logic Programming (LP) and Constraint Programming (CP) paradigms, specifically Constraint Logic Programming (CLP). The LP paradigm presents a declarative approach to programming, based on formal reasoning processes, more appropriate to the resolution of certain types of problems. CLP allows for an efficient approach to constraint satisfaction problems and optimization problems, modeling them in a direct and elegant manner.

Learning outcomes and competences

At the end of this course, students should:

  • Be familiar with declarative programming paradigms, namely LP and CLP.
  • Identify classes of problems where LP and CLP are particularly relevant.
  • Possess abstract reasoning skills and the ability to solve problems in a declarative manner.
  • Be able to correctly apply LP and CLP techniques.
  • Be able to build full Prolog applications, with and without constraints.

Program

  • Logic Programming
    • Propositional and predicate logic. Horn clauses. Unification. Resolution.
    • Clauses. Predicates. Facts. Queries. Rules. Logic variables. Instantiation.
    • LP and databases. Recursion. Lists. Trees. Symbolic expressions.
    • Computation model. Unification. Abstract interpreter. Traces. Search trees. Negation.
  • The Prolog Language
    • Language Elements.
    • Execution model. Backtracking. Termination.
    • Arithmetic. Iteration. Term processing. Operators.
    • Meta- and extra-logical predicates.
    • Non-deterministic programming. Incomplete structures. Meta-interpreters. Search techniques.
  • Constraint Programming
    • Combinatorial problems. Mathematical, linear, and integer programming.
    • Constraints, satisfaction, propagation, and consistency maintenance.
    • Constraints in Boolean, finite and real domains.
    • Optimization. Solution search. Complete and incomplete methods.
    • Languages.
  • Constraint Logic Programming
    • Modeling problems in CLP.
    • CLP using SICStus Prolog.

Bibliography

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