67,408 research outputs found
Harnessing Incremental Answer Set Solving for Reasoning in Assumption-Based Argumentation
Peer reviewe
Componential analysis
Componential analysis is a method of semantic analysis based on the assumption that the meaning of words can be adequately described by a set of primitive semantic features
Reasoning over Assumption-Based Argumentation Frameworks via Answer Set Programming
Formal argumentation is a vibrant research area within artificial intelligence, in particular in knowledge representation and reasoning. Computational models of argumentation are divided into abstract and structured formalisms. Since its introduction in 1995, abstract argumentation, where the structure of arguments is abstracted away, has been much studied and applied. Structured argumentation formalisms, on the other hand, contain the explicit derivation of arguments. This is motivated by the importance of the construction of arguments in the application of argumentation formalisms, but also makes structured formalisms conceptually and often computationally more complex than abstract argumentation.
The focus of this work is on assumption-based argumentation (ABA), a major structured formalism. Specifically we address the relative lack of efficient computational tools for reasoning in ABA compared to abstract argumentation. The computational efficiency of ABA reasoning systems has been markedly lower than the systems for abstract argumentation. In this thesis we introduce a declarative approach to reasoning in ABA via answer set programming (ASP), drawing inspiration from existing tools for abstract argumentation. In addition, we consider ABA+, a generalization of ABA that incorporates preferences into the formalism. The complexity of reasoning in ABA+ is higher than in ABA for most problems. We are able to extend our declarative approach to some ABA+ reasoning problems. We show empirically that our approach vastly outperforms previous reasoning systems for ABA and ABA+
The Satisfiability Problem for Boolean Set Theory with a Choice Correspondence
Given a set U of alternatives, a choice (correspondence) on U is a
contractive map c defined on a family Omega of nonempty subsets of U.
Semantically, a choice c associates to each menu A in Omega a nonempty subset
c(A) of A comprising all elements of A that are deemed selectable by an agent.
A choice on U is total if its domain is the powerset of U minus the empty set,
and partial otherwise. According to the theory of revealed preferences, a
choice is rationalizable if it can be retrieved from a binary relation on U by
taking all maximal elements of each menu. It is well-known that rationalizable
choices are characterized by the satisfaction of suitable axioms of
consistency, which codify logical rules of selection within menus. For
instance, WARP (Weak Axiom of Revealed Preference) characterizes choices
rationalizable by a transitive relation. Here we study the satisfiability
problem for unquantified formulae of an elementary fragment of set theory
involving a choice function symbol c, the Boolean set operators and the
singleton, the equality and inclusion predicates, and the propositional
connectives. In particular, we consider the cases in which the interpretation
of c satisfies any combination of two specific axioms of consistency, whose
conjunction is equivalent to WARP. In two cases we prove that the related
satisfiability problem is NP-complete, whereas in the remaining cases we obtain
NP-completeness under the additional assumption that the number of choice terms
is constant.Comment: In Proceedings GandALF 2017, arXiv:1709.01761. "extended" version at
arXiv:1708.0612
The satisfiability problem for Boolean set theory with a choice correspondence (Extended version)
Given a set of alternatives, a choice (correspondence) on is a
contractive map defined on a family of nonempty subsets of .
Semantically, a choice associates to each menu a nonempty
subset comprising all elements of that are deemed
selectable by an agent. A choice on is total if its domain is the powerset
of minus the empty set, and partial otherwise. According to the theory of
revealed preferences, a choice is rationalizable if it can be retrieved from a
binary relation on by taking all maximal elements of each menu. It is
well-known that rationalizable choices are characterized by the satisfaction of
suitable axioms of consistency, which codify logical rules of selection within
menus. For instance, WARP (Weak Axiom of Revealed Preference) characterizes
choices rationalizable by a transitive relation. Here we study the
satisfiability problem for unquantified formulae of an elementary fragment of
set theory involving a choice function symbol , the Boolean set
operators and the singleton, the equality and inclusion predicates, and the
propositional connectives. In particular, we consider the cases in which the
interpretation of satisfies any combination of two specific axioms
of consistency, whose conjunction is equivalent to WARP. In two cases we prove
that the related satisfiability problem is NP-complete, whereas in the
remaining cases we obtain NP-completeness under the additional assumption that
the number of choice terms is constant
An LTL Semantics of Business Workflows with Recovery
We describe a business workflow case study with abnormal behavior management
(i.e. recovery) and demonstrate how temporal logics and model checking can
provide a methodology to iteratively revise the design and obtain a correct-by
construction system. To do so we define a formal semantics by giving a
compilation of generic workflow patterns into LTL and we use the bound model
checker Zot to prove specific properties and requirements validity. The working
assumption is that such a lightweight approach would easily fit into processes
that are already in place without the need for a radical change of procedures,
tools and people's attitudes. The complexity of formalisms and invasiveness of
methods have been demonstrated to be one of the major drawback and obstacle for
deployment of formal engineering techniques into mundane projects
On computing explanations in argumentation
Copyright © 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.Argumentation can be viewed as a process of generating explanations. However, existing argumentation semantics are developed for identifying acceptable arguments within a set, rather than giving concrete justifications for them. In this work, we propose a new argumentation semantics, related admissibility, designed for giving explanations to arguments in both Abstract Argumentation and Assumption-based Argumentation. We identify different types of explanations defined in terms of the new semantics. We also give a correct computational counterpart for explanations using dispute forests
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