Abstract
Computational models of argumentation [1] are approaches for non-monotonic reasoning that focus on the interplay between arguments and counterarguments in order to reach conclusions.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Atkinson, K., et al.: Toward artificial argumentation. AI Mag. 38(3), 25–36 (2017)
Besnard, P., Hunter, A.: Constructing argument graphs with deductive arguments: a tutorial. Argum. Comput. 5(1), 5–30 (2014)
Biere, A., Heule, M., van Maaren, H., Walsh, T. (eds.): Handbook of Satisfiability. Frontiers in Artificial Intelligence and Applications, vol. 185. IOS Press, Amsterdam (2009)
Cerutti, F., Gaggl, S.A., Thimm, M., Wallner, J.P.: Foundations of implementations for formal argumentation. In: Baroni, P., Gabbay, D., Giacomin, M., van der Torre, L. (eds.) Handbook of Formal Argumentation, chap. 15. College Publications, February 2018. Also appears in IfCoLog J. Log. Appl. 4(8), 2623–2706, October 2017
Cerutti, F., Giacomin, M., Vallati, M.: ArgSemSAT: solving argumentation problems using SAT. In: Computational Models of Argument - Proceedings of COMMA 2014, Atholl Palace Hotel, Scottish Highlands, UK, 9–12 September 2014, pp. 455–456 (2014)
Charwat, G., Dvořák, W., Gaggl, S.A., Wallner, J.P., Woltran, S.: Methods for solving reasoning problems in abstract argumentation - a survey. Artif. Intell. 220, 28–63 (2015)
Dimopoulos, Y., Nebel, B., Toni, F.: On the computational complexity of assumption-based argumentation for default reasoning. Artif. Intell. 141(1), 57–78 (2002)
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, chap. 14. College Publications, February 2018
Egly, U., Gaggl, S.A., Woltran, S.: Answer-set programming encodings for argumentation frameworks. Technical report DBAI-TR-2008-62, Technische Universität Wien (2008)
Gabbay, D., Rodrigues, O.: A self-correcting iteration schema for argumentation networks. In: Proceedings of the Fifth International Conference on Computational Models of Argumentation (COMMA 2014) (2014)
Gaggl, S.A., Manthey, N.: ASPARTIX-D: ASP argumentation reasoning tool - dresden. In: System Descriptions of the First International Competition on Computational Models of Argumentation (ICCMA 2015). ArXiv (2015)
GarcÃa, A.J., Simari, G.R.: Defeasible logic programming: DeLP-servers, contextual queries, and explanations for answers. Argum. Comput. 5(1), 63–88 (2014)
Gebser, M., Kaminski, R., Kaufmann, B., Schaub, T.: Answer Set Solving in Practice. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, San Rafael (2012)
Geilen, N., Thimm, M.: Heureka: a general heuristic backtracking solver for abstract argumentation. In: Black, E., Modgil, S., Oren, N. (eds.) TAFA 2017. LNCS (LNAI), vol. 10757, pp. 143–149. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75553-3_10
Modgil, S., Prakken, H.: The ASPIC+ framework for structured argumentation: a tutorial. Argum. Comput. 5, 31–62 (2014)
Nofal, S., Atkinson, K., Dunne, P.E.: Looking-ahead in backtracking algorithms for abstract argumentation. Int. J. Approx. Reason. 78, 265–282 (2016)
Rodrigues, O.: A forward propagation algorithm for the computation of the semantics of argumentation frameworks. In: Black, E., Modgil, S., Oren, N. (eds.) TAFA 2017. LNCS (LNAI), vol. 10757, pp. 120–136. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-75553-3_8
Snaith, M., Reed, C.: TOAST: online ASPIC+ implementation. In: Proceedings of the Fourth International Conference on Computational Models of Argument (COMMA 2012), pp. 509–510. IOS Press (2012)
Thimm, M.: Stochastic local search algorithms for abstract argumentation under stable semantics. In: Modgil, S., Budzynska, K., Lawrence, J. (eds.) Proceedings of the Seventh International Conference on Computational Models of Argumentation (COMMA 2018). Frontiers in Artificial Intelligence and Applications, Warsaw, Poland, vol. 305, pp. 169–180, September 2018
Thimm, M., Rienstra, T.: Approximate reasoning with ASPIC+ by argument sampling (2019, under review)
Toni, F.: A tutorial on assumption-based argumentation. Argum. Comput. 5(1), 89–117 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Thimm, M. (2019). Algorithmic Approaches to Computational Models of Argumentation. In: Cuzzocrea, A., Greco, S., Larsen, H., Saccà , D., Andreasen, T., Christiansen, H. (eds) Flexible Query Answering Systems. FQAS 2019. Lecture Notes in Computer Science(), vol 11529. Springer, Cham. https://doi.org/10.1007/978-3-030-27629-4_4
Download citation
DOI: https://doi.org/10.1007/978-3-030-27629-4_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-27628-7
Online ISBN: 978-3-030-27629-4
eBook Packages: Computer ScienceComputer Science (R0)