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Representing argumentation schemes with Constraint Handling Rules (CHR)

: Gordon, Thomas F.; Friedrich, Horst; Walton, Douglas

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Argument & computation 9 (2018), Nr.2, S.91-119
ISSN: 1946-2166
ISSN: 1946-2174
Zeitschriftenaufsatz, Elektronische Publikation
Fraunhofer FOKUS ()
argumentation scheme; argument generation; rule-based system; constraint handling rule; logic programming; data protection

We present a high-level declarative programming language for representing argumentation schemes, where schemes represented in this language can be easily validated by domain experts, including developers of argumentation schemes in informal logic and philosophy, and serve as executable specifications for automatically constructing arguments, when applied to a set of assumptions. Since argumentation schemes are defeasible inference rules, both premises and conclusions of schemes can be second-order schema variables, i.e. without a fixed predicate symbol. Thus, while particular schemes can be and have been implemented in computer programs, in general argumentation schemes cannot be represented as executable specifications using logic programming languages based on first-order logic, such as Prolog. Moreover, even if the conclusion (head) of Prolog rules could be second-order variables, a depth-first, backward-chaining search strategy, as typically used in logic programming, would usually cause such programs to not terminate, since every goal would match the head of such a scheme, including all goals created by instantiating the body of the same scheme. The language for representing argumentation schemes presented here, for the purpose of automatically constructing arguments, uses Constraint Handling Rules (CHR), a declarative, Turing complete, forwards-chaining, rule-based programming language introduced by Thom Frühwirth in 1991. CHR is attractive for representing and implementing argumentation for several reasons, including: 1) Inference rules, rewrite rules, sequents, proof rules, and logical axioms can be directly written in CHR. 2) The execution of CHR rules can be interrupted and restarted at any time, with intermediate results approximating the final solution, and 3) Constraints can be input incrementally as they become known, during rule execution, without requiring recomputation. These three properties of CHR appear attractive for representing and implementing argumentation schemes. Since argumentation schemes are (defeasible) inference rules, the ability of CHR to represent inference rules directly would appear to be quite useful. The ability to stop the computation and produce approximate results is compatible with one objective of argumentation, to provide a principled method for supporting approximate reasoning with limited resources. Because argumentation typically takes place in dialogs, with evidence and arguments brought forward and asserted by the participants incrementally, during the course of the dialog, CHR’s ability to handle new information, incrementally introduced during the computation, may be useful. This new rule language for representing argumentation schemes is validated by using it to represent twenty representative argumentation schemes.