Abstract
Abstract dialectical frameworks (ADFs) are a well-studied generalisation of the prominent argumentation frameworks due to Phan Minh Dung. In this paper we propose to use reduced ordered binary decision diagrams (roBDDs) as a suitable representation of the acceptance conditions of arguments within ADFs. We first show that computational complexity of reasoning on ADFs represented by roBDDs is milder than in the general case, with a drop of one level in the polynomial hierarchy. Furthermore, we present a framework to systematically define heuristics for search space exploitation, based on easily retrievable properties of roBDDs and the recently proposed approach of weighted faceted navigation for answer set programming. Finally, we present preliminary experiments of an implementation of our approach showing promise both when compared to state-of-the-art solvers and when developing heuristics for reasoning.
This work is partly supported by the BMBF, Grant 01IS20056_NAVAS, by the Center for Scalable Data Analytics and Artificial Intelligence (ScaDS.AI), and by the DFG through the Collaborative Research Center, Grant TRR 248 project ID 38 9792660.
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References
Al-Abdulkarim, L., Atkinson, K., Bench-Capon, T.J.M.: A methodology for designing systems to reason with legal cases using abstract dialectical frameworks. Artif. Intell. Law 24(1), 1–49 (2016)
Atkinson, K., et al.: Towards artificial argumentation. AI Mag. 38(3), 25–36 (2017)
Baroni, P., Gabbay, D., Giacomin, M., van der Torre, L. (eds.) Handbook of Formal Argumentation. College Publications (2018)
Beneš, N., Brim, L., Kadlecaj, J., Pastva, S., Šafránek, D.: AEON: attractor bifurcation analysis of parametrised Boolean networks. In: Lahiri, S.K., Wang, C. (eds.) CAV 2020. LNCS, vol. 12224, pp. 569–581. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-53288-8_28
Bollig, B., Wegener, I.: Improving the variable ordering of OBDDs is NP-complete. IEEE Trans. Comput. 45(9), 993–1002 (1996)
Brewka, G., Diller, M., Heissenberger, G., Linsbichler, T., Woltran, S.: Solving advanced argumentation problems with answer set programming. Theory Pract. Log. Program. 20(3), 391–431 (2020)
Brewka, G., Ellmauthaler, S., Strass, H., Wallner, J.P., Woltran., S.: Abstract dialectical frameworks. In Baroni, P., Gabbay, D., Giacomin, M., van der Torre, L. (eds.) Handbook of Formal Argumentation, pp. 237–285. College Publications (2018)
Bryant, R.E.: Graph-based algorithms for Boolean function manipulation. IEEE Trans. Comput. 100(8), 677–691 (1986)
Cabrio, E., Villata, S.: Abstract dialectical frameworks for text exploration. In: Proceedings of ICAART, pp. 85–95. SciTePress (2016)
Darwiche, A., Marquis, P.: A knowledge compilation map. J. Artif. Intell. Res. 17, 229–264 (2002)
Diller, M., Wallner, J.P., Woltran, S.: Reasoning in abstract dialectical frameworks using quantified Boolean formulas. Argument Comput. 6(2), 149–177 (2015)
Dung, P.M.: On the acceptability of arguments and its fundamental role in nonmonotonic reasoning, logic programming and n-person games. Artif. Intell. 77(2), 321–358 (1995)
Dvořák, W., Dunne, P.E.: Computational problems in formal argumentation and their complexity. In: Baroni, P., Gabbay, D., Giacomin, M., van der Torre, L. (eds.) Handbook of Formal Argumentation, pp. 631–688. College Publications (2018)
Ellmauthaler, S., Wallner, J.P.: Evaluating Abstract Dialectical Frameworks with ASP. In: Proceedings of COMMA, vol. 245, pp. 505–506. IOS Press (2012)
Fichte, J.K., Gaggl, S.A., Rusovac, D.: Rushing and strolling among answer sets - navigation made easy. In: Proceedings of AAAI (2022)
Gaggl, S.A., Rudolph, S., Straß, H.: On the decomposition of abstract dialectical frameworks and the complexity of naive-based semantics. J. Artif. Intell. Res. 70, 1–64 (2021)
Lai, Y., Liu, D., Wang, S.: Reduced ordered binary decision diagram with implied literals: a new knowledge compilation approach. Knowl. Inf. Syst. 35(3), 665–712 (2013)
Linsbichler, T., Maratea, M., Niskanen, A., Wallner, J.P., Woltran, S.: Advanced algorithms for abstract dialectical frameworks based on complexity analysis of subclasses and SAT solving. Artif. Intell. 307, 103697 (2022)
Marek, V.W., Truszczyński, M.: Stable models and an alternative logic programming paradigm. In: The Logic Programming Paradigm: A 25-Year Perspective. Artificial Intelligence, pp. 375–398 (1999)
Neugebauer, D.: Generating defeasible knowledge bases from real-world argumentations using D-BAS. In: Proceedings of AI \(\hat{\,}\)3@AI*IA. Volume 2012 of CEUR Workshop Proceedings, pp. 105–110. CEUR-WS.org (2017)
Sieling, D.: On the existence of polynomial time approximation schemes for OBDD minimization. In: Morvan, M., Meinel, C., Krob, D. (eds.) STACS 1998. LNCS, vol. 1373, pp. 205–215. Springer, Heidelberg (1998). https://doi.org/10.1007/BFb0028562
Strass, H.: Instantiating rule-based defeasible theories in abstract dialectical frameworks and beyond. J. Log. Comput. 28(3), 605–627 (2018)
Strass, H., Ellmauthaler, S.: goDIAMOND 0.6.6 - ICCMA 2017 system description. In: 2nd ICCMA (2017)
Strass, H., Wallner, J.P.: Analyzing the computational complexity of abstract dialectical frameworks via approximation fixpoint theory. Artif. Intell. 226, 34–74 (2015)
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Ellmauthaler, S., Gaggl, S.A., Rusovac, D., Wallner, J.P. (2022). Representing Abstract Dialectical Frameworks with Binary Decision Diagrams. In: Gottlob, G., Inclezan, D., Maratea, M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2022. Lecture Notes in Computer Science(), vol 13416. Springer, Cham. https://doi.org/10.1007/978-3-031-15707-3_14
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