Automated Reasoning

Prof. Agostino Dovier

Current detailed program:
  • A.A. 2020/2021
  • Previous programs since 2015/16 differ slightly from the current one. Abstract The main languages and techniques for knowledge representation and reasoning will be presented, focusing in particular on logic languages such as Answer Set Programming, Action Description Languages for planning, and the constraint modeling language Minizinc. Those languages are commonly used for modeling and solving combinatorial optimization problems, and for programming intelligent systems in a multi-disciplinary context. The main techniques for constraint-based solution search will be presented and compared. Paradigms will be presented either at a theoretical level or at a practical level, modeling and solving several benchmark problems.
    Automated Reasoning is a subfield of ``Intelligent Systems'' (CS2013-final-report IEEE/ACM).

    Detailed programs of the ancestor course called Constraint Programming & Planning (slides in Italian):



    Constraint Programming Part

    1. Handbook of Constraint Programming By Francesca Rossi, Peter van Beek amd Toby Walsh. Elsevier, 2006. (look for free pdf on-line, e.g. HERE)
    2. R. Bartak On-line guide to constraint Programming.
    3. Willem-Jan van Hoeve. The Alldifferent Constraint: A Survey 2001
    4. Minizinc Tutorial, by Kim Marriott and Peter J. Stuckey.

    Logic Programming Part

    1. J. W. Lloyd. Foundations of Logic Programming. Springer. 1984 (look for free pdf on-line, e.g. HERE) OLD, but the reference for the basics of the semantics part.
    2. K.R. Apt. From Logic Programming to Prolog. International Series in Computer Science. Prentice Hall, 1997. As LLloyd's book, a classical. And helps you learning conversion of ps to pdf
    3. M. Gelfond and Y. Kahl Knowledge Representation, Reasoning, and the Design of Intelligent Agents The Answer-Set Programming Approach. Cambridge University Press, 2014.
    4. Teaching Answer Set Programming By Univ. of Potsdam team (chaired by Torsten Schaub).
    5. Answer Set Solving in Practice by Martin Gebser, Roland Kaminski, Benjamin Kaufmann, and Torsten Schaub
      And also this free course Answer Set Solving in Practice related to the same material.
    6. Knowledge representation, reasoning and declarative problem solving. C Baral. Cambridge university press, 2003.
    7. Thomas Eiter and Georg Gottlob. On the Computational Cost of Disjunctive Logic Programming: Propositional Case. Annals of Mathematics and Artificial Intelligence, 15(3/4):289-323, 1995.

    Other material

    1. A. Dovier, A. Formisano. Dispense per il corso (in Italian!)
    2. A. Dovier, A. Formisano, E. Pontelli.
      Perspectives on Logic-based Approaches for Reasoning About Actions and Change.
      In Logic Programming, Knowledge Representation, and Nonmonotonic Reasoning, Essays Dedicated to Michael Gelfond on the Occasion of His 65th Birthday M. Balduccini and T.C. Son, eds., LNCS 6565, pp. 259-279, (DRAFT), 2011.
    3. K. Marriott and P. Stuckey. Programming with Constraints. The MIT Press, 1998.
    4. K.R. Apt. Principles of constraint programming.Cambridge University Press, 2003.
    5. L. Sterling and E. Shapiro. The Art of Prolog. 2nd ed., The MIT Press 1994,
    6. Marco Gavanelli Un tool per produrre SLD (NF) trees pronti per il latex da computazioni ECLIPSE.
    7. Krzysztof R. Apt and Mark Wallace. Constraint Logic Programming using Eclipse
    8. Some scientific articles that can be of interest
    9. T. Fruhwirth and S. Abdennadher. Essentials of constraint programming. Springer Verlag, 2002. Logic Programming by K.R. Apt. Handbook of Theoretical Computer Science, Volume B: Formal Models and Semantics. Pages 493-574, 1990.