Skip to main content

A Bird’s-Eye View of Forgetting in Answer-Set Programming

  • Conference paper
  • First Online:
Logic Programming and Nonmonotonic Reasoning (LPNMR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10377))

Abstract

Forgetting is an operation that allows the removal, from a knowledge base, of middle variables no longer deemed relevant, while preserving all relationships (direct and indirect) between the remaining variables. When investigated in the context of Answer-Set Programming, many different approaches to forgetting have been proposed, following different intuitions, and obeying different sets of properties.

This talk will present a bird’s-eye view of the complex landscape composed of the properties and operators of forgetting defined over the years in the context of Answer-Set Programming, zooming in on recent findings triggered by the formulation of the so-called strong persistence, a property based on the strong equivalence between an answer-set program and the result of forgetting modulo the forgotten atoms, which seems to best encode the requirements of the forgetting operation.

The author was partially supported by FCT UID/CEC/04516/2013. This paper is substantially based on [1, 2].

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    See Appendix for definitions and notation on Answer-Set Programming.

  2. 2.

    Unless stated otherwise, \(\mathsf {F}\) is a class of forgetting operators, and \(\mathcal {C}\) the class of programs over \(\mathcal {A}\) of a given \(\mathsf {f}\in \mathsf {F}\).

  3. 3.

    An additional set of properties was introduced in [29]. The reader is referred to [36, 37] for a detailed discussion regarding these properties.

  4. 4.

    (SP) \(_{\langle P,V\rangle }\) is a restriction of property (SP) to specific forgetting instances. A forgetting operator \({\mathsf {f}}\) over \(\mathcal {C}\) satisfies (SP) \(_{\langle P,V\rangle }\) if \(\mathcal {AS}(\mathsf {f}(P,V)\cup R)=\mathcal {AS}(P\cup R)_{\parallel V}\), for all programs \(R\in \mathcal {C}\) with \(\mathcal {A}(R)\subseteq \mathcal {A}\setminus V\).

  5. 5.

    Often, the term propositional variable is used synonymously.

  6. 6.

    Extended logic programs [44] are actually more expressive, but this form is sufficient here.

References

  1. Goncalves, R., Knorr, M., Leite, J.: The ultimate guide to forgetting in answer set programming. In: Baral, C., Delgrande, J., Wolter, F. (eds.) Proceedings of KR, pp. 135–144. AAAI Press (2016)

    Google Scholar 

  2. Gonçalves, R., Knorr, M., Leite, J.: You can’t always forget what you want: on the limits of forgetting in answer set programming. In: Fox, M.S., Kaminka, G.A. (eds.) Proceedings of ECAI. IOS Press (2016)

    Google Scholar 

  3. European Parliament: General data protection regulation. Official Journal of the European Union L119/59, May 2016

    Google Scholar 

  4. Lin, F., Reiter, R.: How to progress a database. Artif. Intell. 92(1–2), 131–167 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  5. Liu, Y., Wen, X.: On the progression of knowledge in the situation calculus. In: Walsh, T. (ed.) Proceedings of IJCAI, IJCAI/AAAI, pp. 976–982 (2011)

    Google Scholar 

  6. Rajaratnam, D., Levesque, H.J., Pagnucco, M., Thielscher, M.: Forgetting in action. In: Baral, C., Giacomo, G.D., Eiter, T. (eds.) Proceedings of KR. AAAI Press (2014)

    Google Scholar 

  7. Lang, J., Liberatore, P., Marquis, P.: Propositional independence: formula-variable independence and forgetting. J. Artif. Intell. Res. (JAIR) 18, 391–443 (2003)

    MathSciNet  MATH  Google Scholar 

  8. Zhang, Y., Foo, N.Y.: Solving logic program conflict through strong and weak forgettings. Artif. Intell. 170(8–9), 739–778 (2006)

    Article  MathSciNet  Google Scholar 

  9. Eiter, T., Wang, K.: Semantic forgetting in answer set programming. Artif. Intell. 172(14), 1644–1672 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  10. Lang, J., Marquis, P.: Reasoning under inconsistency: a forgetting-based approach. Artif. Intell. 174(12–13), 799–823 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  11. Wang, Z., Wang, K., Topor, R.W., Pan, J.Z.: Forgetting for knowledge bases in DL-Lite. Ann. Math. Artif. Intell. 58(1–2), 117–151 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  12. Kontchakov, R., Wolter, F., Zakharyaschev, M.: Logic-based ontology comparison and module extraction, with an application to dl-lite. Artif. Intell. 174(15), 1093–1141 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  13. Konev, B., Ludwig, M., Walther, D., Wolter, F.: The logical difference for the lightweight description logic EL. J. Artif. Intell. Res. (JAIR) 44, 633–708 (2012)

    MATH  Google Scholar 

  14. Konev, B., Lutz, C., Walther, D., Wolter, F.: Model-theoretic inseparability and modularity of description logic ontologies. Artif. Intell. 203, 66–103 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  15. Lewis, C.I.: A survey of symbolic logic. University of California Press (1918). Republished by Dover (1960)

    Google Scholar 

  16. Bledsoe, W.W., Hines, L.M.: Variable elimination and chaining in a resolution-based prover for inequalities. In: Bibel, W., Kowalski, R. (eds.) CADE 1980. LNCS, vol. 87, pp. 70–87. Springer, Heidelberg (1980). doi:10.1007/3-540-10009-1_7

    Google Scholar 

  17. Larrosa, J.: Boosting search with variable elimination. In: Dechter, R. (ed.) CP 2000. LNCS, vol. 1894, pp. 291–305. Springer, Heidelberg (2000). doi:10.1007/3-540-45349-0_22

    Chapter  Google Scholar 

  18. Larrosa, J., Morancho, E., Niso, D.: On the practical use of variable elimination in constraint optimization problems: ‘still-life’ as a case study. J. Artif. Intell. Res. (JAIR) 23, 421–440 (2005)

    MATH  Google Scholar 

  19. Middeldorp, A., Okui, S., Ida, T.: Lazy narrowing: strong completeness and eager variable elimination. Theor. Comput. Sci. 167(1&2), 95–130 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  20. Moinard, Y.: Forgetting literals with varying propositional symbols. J. Log. Comput. 17(5), 955–982 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  21. Weber, A.: Updating propositional formulas. In: Expert Database Conference, pp. 487–500 (1986)

    Google Scholar 

  22. Alferes, J.J., Leite, J.A., Pereira, L.M., Przymusinska, H., Przymusinski, T.C.: Dynamic updates of non-monotonic knowledge bases. J. Logic Program. 45(1–3), 43–70 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  23. Eiter, T., Fink, M., Sabbatini, G., Tompits, H.: On properties of update sequences based on causal rejection. Theor. Pract. Logic Program. (TPLP) 2(6), 721–777 (2002)

    MathSciNet  MATH  Google Scholar 

  24. Sakama, C., Inoue, K.: An abductive framework for computing knowledge base updates. Theor. Pract. Logic Program. (TPLP) 3(6), 671–713 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  25. Slota, M., Leite, J.: Robust equivalence models for semantic updates of answer-set programs. In: Brewka, G., Eiter, T., McIlraith, S.A. (eds.) Proceeding of KR, pp. 158–168. AAAI Press (2012)

    Google Scholar 

  26. Slota, M., Leite, J.: A unifying perspective on knowledge updates. In: Cerro, L.F., Herzig, A., Mengin, J. (eds.) JELIA 2012. LNCS, vol. 7519, pp. 372–384. Springer, Heidelberg (2012). doi:10.1007/978-3-642-33353-8_29

    Chapter  Google Scholar 

  27. Delgrande, J.P., Schaub, T., Tompits, H., Woltran, S.: A model-theoretic approach to belief change in answer set programming. ACM Trans. Comput. Log. 14(2), 14 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  28. Slota, M., Leite, J.: The rise and fall of semantic rule updates based on SE-models. TPLP 14(6), 869–907 (2014)

    MathSciNet  MATH  Google Scholar 

  29. Wong, K.S.: Forgetting in Logic Programs. Ph.D. thesis, The University of New South Wales (2009)

    Google Scholar 

  30. Wang, Y., Zhang, Y., Zhou, Y., Zhang, M.: Forgetting in logic programs under strong equivalence. In: Brewka, G., Eiter, T., McIlraith, S.A. (eds.) Proceedings of KR, pp. 643–647. AAAI Press (2012)

    Google Scholar 

  31. Wang, Y., Wang, K., Zhang, M.: Forgetting for answer set programs revisited. In: Rossi, F. (ed.) Proceedings of IJCAI, IJCAI/AAAI (2013)

    Google Scholar 

  32. Knorr, M., Alferes, J.J.: Preserving strong equivalence while forgetting. In: Fermé, E., Leite, J. (eds.) JELIA 2014. LNCS, vol. 8761, pp. 412–425. Springer, Cham (2014). doi:10.1007/978-3-319-11558-0_29

    Google Scholar 

  33. Wang, Y., Zhang, Y., Zhou, Y., Zhang, M.: Knowledge forgetting in answer set programming. J. Artif. Intell. Res. (JAIR) 50, 31–70 (2014)

    MathSciNet  MATH  Google Scholar 

  34. Delgrande, J.P., Wang, K.: A syntax-independent approach to forgetting in disjunctive logic programs. In: Bonet, B., Koenig, S. (eds.) Proceedings of AAAI, pp. 1482–1488. AAAI Press (2015)

    Google Scholar 

  35. Zhang, Y., Zhou, Y.: Knowledge forgetting: properties and applications. Artif. Intell. 173(16–17), 1525–1537 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  36. Gonçalves, R., Knorr, M., Leite, J.: Forgetting in ASP: the forgotten properties. In: Michael, L., Kakas, A. (eds.) JELIA 2016. LNCS, vol. 10021, pp. 543–550. Springer, Cham (2016). doi:10.1007/978-3-319-48758-8_37

    Chapter  Google Scholar 

  37. Gonçalves, R., Knorr, M., Leite, J.: On some properties of forgetting in ASP. In: Booth, R., Casini, G., Klarman, S., Richard, G., Varzinczak, I.J. (eds.) Proceedings of the International Workshop on Defeasible and Ampliative Reasoning (DARe-16). CEUR Workshop Proceedings, vol. 1626. CEUR-WS.org (2016)

    Google Scholar 

  38. Brass, S., Dix, J.: Semantics of (disjunctive) logic programs based on partial evaluation. J. Log. Program. 40(1), 1–46 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  39. Wong, K.S.: Sound and complete inference rules for SE-consequence. J. Artif. Intell. Res. (JAIR) 31, 205–216 (2008)

    MathSciNet  MATH  Google Scholar 

  40. Eiter, T., Fink, M., Woltran, S.: Semantical characterizations and complexity of equivalences in answer set programming. ACM Trans. Comput. Log. 8(3) (2007)

    Google Scholar 

  41. Lifschitz, V.: What is answer set programming? In: Fox, D., Gomes, C.P. (eds.) Proceedings of AAAI, pp. 1594–1597. AAAI Press (2008)

    Google Scholar 

  42. Sagiv, Y.: Optimizing datalog programs. In: Minker, J. (ed.) Foundations of Deductive Databases and Logic Programming, pp. 659–698. Morgan Kaufmann (1988)

    Google Scholar 

  43. Eiter, T., Fink, M.: Uniform equivalence of logic programs under the stable model semantics. In: Palamidessi, C. (ed.) ICLP 2003. LNCS, vol. 2916, pp. 224–238. Springer, Heidelberg (2003). doi:10.1007/978-3-540-24599-5_16

    Chapter  Google Scholar 

  44. Lifschitz, V., Tang, L.R., Turner, H.: Nested expressions in logic programs. Ann. Math. Artif. Intell. 25(3–4), 369–389 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  45. Lifschitz, V., Pearce, D., Valverde, A.: Strongly equivalent logic programs. ACM Trans. Comput. Log. 2(4), 526–541 (2001)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

I would like to thank my close colleagues Ricardo Gonçalves and Matthias Knorr for all their dedication and contributions to our joint projects, turning it into a more fun and rewarding ride.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to João Leite .

Editor information

Editors and Affiliations

A Answer-Set Programming

A Answer-Set Programming

We assume a propositional signature \(\mathcal {A}\), a finite set of propositional atomsFootnote 5. An (extended) logic program P over \(\mathcal {A}\) is a finite set of (extended) rules of the form

$$\begin{aligned} a_1 \vee \ldots \vee a_k&\leftarrow b_1,..., b_l, not\,c_{1},..., not\,c_m, not\,not\,d_1,..., not\,not\,d_n \; , \end{aligned}$$
(1)

where all \(a_1,\ldots ,a_k,b_1,\ldots , b_l,c_{1},\ldots , c_m\), and \(d_{1},\ldots , d_n\) are atoms of \(\mathcal {A}\).Footnote 6 Such rules r are also commonly written in a more succinct way as

$$\begin{aligned} A \leftarrow B, not\,C, not\,not\,D \; , \end{aligned}$$
(2)

where we have \( A = \{a_1,\ldots ,a_k\}\), \( B =\{b_1,\ldots , b_l\}\), \( C =\{c_{1},\ldots , c_m\}\), \( D =\{d_{1},\ldots , d_n\}\), and we will use both forms interchangeably. By \(\mathcal {A}(P)\) we denote the set of atoms appearing in P. This class of logic programs, \(\mathcal {C}_{e}\), includes a number of special kinds of rules r: if \(n=0\), then we call r disjunctive; if, in addition, \(k\le 1\), then r is normal; if on top of that \(m=0\), then we call r Horn, and fact if also \(l=0\). The classes of disjunctive, normal and Horn programs, \(\mathcal {C}_{d}\), \(\mathcal {C}_{n}\), and \(\mathcal {C}_{H}\), are defined resp. as a finite set of disjunctive, normal, and Horn rules. We also call extended rules with \(k\le 1\) non-disjunctive, thus admitting a non-standard class \(\mathcal {C}_{nd}\), called non-disjunctive programs, different from normal programs. Given a program P and a set I of atoms, the reduct \(P^I\) is defined as \(P^I = \{ A \leftarrow B : r \text { of the form (2) in } P, C \cap I=\emptyset , D \subseteq I\}\).

An HT-interpretation is a pair \(\langle X,Y\rangle \) s.t. \(X\subseteq Y \subseteq \mathcal {A}\). Given a program P, an HT-interpretation \(\langle X,Y\rangle \) is an HT-model of P if \(Y\,\models \,P\) and \(X\,\models \,P^{Y}\), where \(\models \) denotes the standard consequence relation for classical logic. We admit that the set of HT-models of a program P are restricted to \(\mathcal {A}(P)\) even if \(\mathcal {A}(P)\subset \mathcal {A}\). We denote by \(\mathcal {HT}(P)\) the set of all HT-models of P. A set of atoms Y is an answer set of P if \(\langle Y,Y\rangle \in \mathcal {HT}(P)\), but there is no \(X\subset Y\) such that \(\langle X,Y\rangle \in \mathcal {HT}(P)\). The set of all answer sets of P is denoted by \(\mathcal {AS}(P)\). We say that two programs \(P_1, P_2\) are equivalent if \(\mathcal {AS}(P_1)=\mathcal {AS}(P_2)\) and strongly equivalent, denoted by \(P_1\equiv P_2\), if \(\mathcal {AS}(P_1\cup R)=\mathcal {AS}(P_2\cup R)\) for any \(R\in \mathcal {C}_{e}\). It is well-known that \(P_1\equiv P_2\) exactly when \(\mathcal {HT}(P_1)=\mathcal {HT}(P_2)\) [45]. We say that \(P'\) is an HT-consequence of P, denoted by \(P\,\models _\mathsf{HT}P'\), whenever \(\mathcal {HT}(P)\subseteq \mathcal {HT}(P')\). The V -exclusion of a set of answer sets (a set of HT-interpretations) \(\mathcal {M}\), denoted \(\mathcal {M}_{\parallel V}\), is \({\{X\backslash V\mid X\in \mathcal {M}\}}\) (\({\{\langle X\backslash V,Y\setminus V\rangle \mid \langle X,Y\rangle \in \mathcal {M}\}}\)). Finally, given two sets of atoms \(X,X'\subseteq \mathcal {A}\), we write \(X\sim _V X'\) whenever \(X \backslash V=X' \backslash V\).

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Leite, J. (2017). A Bird’s-Eye View of Forgetting in Answer-Set Programming. In: Balduccini, M., Janhunen, T. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2017. Lecture Notes in Computer Science(), vol 10377. Springer, Cham. https://doi.org/10.1007/978-3-319-61660-5_2

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-61660-5_2

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61659-9

  • Online ISBN: 978-3-319-61660-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics