Guillermo Ricardo Simari

FLAP Journal 2021 Journal Article

On the Incremental Computation of Semantics in Dynamic Argumentation.

• Gianvincenzo Alfano
• Sergio Greco
• Francesco Parisi
• Gerardo I. Simari
• Guillermo Ricardo Simari

Argumentation frameworks often model dynamic situations where arguments and their relationships (e.g., attacks) frequently change over time. As a consequence, the sets of conclusions (e.g., extensions of abstract argumentation frameworks, or warranted literals for structured argumentation frameworks) often need to be computed again after performing an update. However, as most of the argumentation semantics proposed so far suffer from high computational complexity, computing the set of conclusions from scratch is costly in general. In this work, we address the problems of efficiently recomputing extensions of dynamic abstract argumentation frameworks and warranted literals in dynamic defeasible knowledge bases. In particular, we first present an incremental algorithmic solution whose main idea is that of using an initial extension and the update to identify a (potentially small) portion of an abstract argumentation framework, which is sufficient to compute an extension of the updated framework.

FLAP Journal 2021 Journal Article

Preface.

• Dov M. Gabbay
• Massimiliano Giacomin
• Guillermo Ricardo Simari
• Matthias Thimm

ECAI Conference 2020 Conference Paper

Dynamics in Abstract Argumentation Frameworks with Recursive Attack and Support Relations

• Gianvincenzo Alfano
• Andrea Cohen
• Sebastian Gottifredi
• Sergio Greco
• Francesco Parisi
• Guillermo Ricardo Simari

Argumentation is an important topic in the field of AI. There is a substantial amount of work about different aspects of Dung’s abstract Argumentation Framework (AF). Two relevant aspects considered separately so far are extending the framework to account for recursive attacks and supports, and considering dynamics, i. e. , AFs evolving over time. In this paper, we jointly deal with these two aspects. We focus on Attack-Support Argumentation Frameworks (ASAFs) which allow for attack and support relations not only between arguments but also targeting attacks and supports at any level, and propose an approach for the incremental computation of extensions (sets of accepted arguments, attacks and supports) of updated ASAFs. Our approach assumes that an initial ASAF extension is given and uses it for first checking whether updates are irrelevant; for relevant updates, an extension of an updated ASAF is computed by translating the problem to the AF domain and leveraging on AF solvers. We experimentally show our incremental approach outperforms the direct computation of extensions for updated ASAFs.

KR Conference 2018 Conference Paper

An Incremental Approach to Structured Argumentation over Dynamic Knowledge Bases

• Gianvincenzo Alfano
• Sergio Greco
• Francesco Parisi
• Gerardo Ignacio Simari
• Guillermo Ricardo Simari

Considering the structure of arguments allows users to analyze reasons for and against a conclusion; the warrant status of such a conclusion in the context of a knowledge base represents the main output of a dialectical process. A naive approach to computing such statuses is costly, and any update to the knowledge base potentially has a huge impact if done in this manner. We study the case of updates consisting of both additions and removals of pieces of knowledge in the Defeasible Logic Programming (DeLP) framework, first analyzing the complexity of the problem and then identifying conditions under which we can avoid unnecessary computations— central to this is the development of data structures to keep track of which results can potentially be affected by a given update. We also present experiments showing that our incremental algorithm yields significantly lower running times in practice, as well as overall fewer recomputations.

ECAI Conference 2014 Conference Paper

Inconsistency resolution and global conflicts

• Cristhian A. D. Deagustini
• Maria Vanina Martinez
• Marcelo A. Falappa
• Guillermo Ricardo Simari

Over the years, inconsistency management has caught the attention of researchers of different areas. Inconsistency is a problem that arises in many different scenarios, for instance, ontology development or knowledge integration. In such settings, it is important to have adequate automatic tools for handling conflicts that may appear in a knowledge base. We introduce an approach to consolidation of belief bases based on a refinement of kernel contraction that accounts for the relation among kernels using clusters instead. We define cluster contraction-based consolidation operators contraction by falsum on a belief base using cluster incision functions, a refinement of kernel incision functions.

KR Conference 2012 Short Paper

Modelling Time and Reliability in Structured Argumentation Frameworks

• Maximiliano Celmo David Budán
• Mauro Gómez Lucero
• Carlos Iván Chesñevar
• Guillermo Ricardo Simari

TAF are associated with availability intervals, their attacks are assumed to be static and permanent in time. In this paper we introduce a novel framework, called Extended Temporal Argumentation Framework (E-TAF), extending TAF with the capability of modeling the availability of attacks among arguments. This additional feature of E-TAF allows for instance to model reliability of arguments varying over time, where an attack can be only available in a given time interval (meaning that the attacking argument is more reliable than the attacked one on this interval). We show how E-TAF can on its turn be enriched by considering Structured Abstract Argumentation, adding compositional elements to the abstract arguments involved based on a simplified version of the recently introduced Dynamic Argumentation Frameworks (Rotstein et al. 2010). In this formalization arguments are conceived as structures standing for chains (or trees) of smaller abstract entities representing individual reasoning steps. We will show that the resulting framework E-TAF∗ is powerful enough to provide a suitable model for different time-dependent issues (e. g. reliability) associated with arguments, with application in several real-world situations. The central contribution of this paper is thus to advance in the integration of time and reliability in the context of argumentation systems. We are interested in preserving as much as possible the generality of the approach, maintaining it independent from any particular representation language and considering as well the internal structure of the arguments involved. Argumentation is a human-like reasoning mechanism contributing to the formalization of commonsense reasoning. In the last decade, several argument-based formalisms have emerged, with application in many areas, such as legal reasoning, autonomous agents and multi-agent systems; many are based on Dung’s seminal work characterizing Abstract Argumentation Frameworks (AF). Recent research in the area has led to Temporal Argumentation Frameworks (TAF) that extend Dung’s by considering the temporal availability of arguments. In this work we introduce a novel framework, called Extended Temporal Argumentation Framework (E-TAF), extending TAF with the capability of modeling availability of attacks among arguments, which allows for instance to model reliability of arguments varying over time. We show how E-TAF can be enriched by considering Structured Abstract Argumentation, adding compositional elements to the abstract arguments involved based on a simplified version of the recently introduced Dynamic Argumentation Frameworks.

ECAI Conference 2010 Conference Paper

On Admissibility in Timed Abstract Argumentation Frameworks

• Maria Laura Cobo
• Diego C. Martínez 0001
• Guillermo Ricardo Simari

In this work, we define Timed Abstract Argumentation Frameworks, a novel argumentation formalism where arguments are only valid for consideration in a given period of time, which is defined for every individual argument. Thus, the attainability of attacks and defenses is related to time, and the outcome of the framework may vary accordingly. We define a timed, interval-based notion of grounded extension as a skeptical semantics.

IJCAI Conference 2007 Conference Paper

• Carlos Iv
• aacute; n Ches
• ntilde; evar
• Guillermo Ricardo Simari

This paper introduces a novel approach to model warrant computation in a skeptical abstract argumentation framework. We show that such search space can be defined as a lattice, and illustrate how the so-called dialectical constraints can play a role for guiding the efficient computation of warranted arguments.

LPAR Conference 2006 Conference Paper

Representing Defaults and Negative Information Without Negation-as-Failure

• Pablo R. Fillottrani
• Guillermo Ricardo Simari

Abstract In logic programs, negation-as-failure has been used both for representing negative information and for providing default nonmonotonic inference. In this paper we argue that this twofold role is not only unnecessary for the expressiveness of the language, but it also plays against declarative programming, especially if further negation symbols such as strong negation are also available. We therefore propose a new logic programming approach in which negation and default inference are independent, orthogonal concepts. Semantical characterization of this approach is given in the style of answer sets, but other approaches are also possible. Finally, we compare them with the semantics for logic programs with two kinds of negation.

EUMAS Conference 2005 Conference Paper

Expansion Operators for Modelling Agent Reasoning in Possibilistic Defeasible Logic Programming

• Carlos Iván Chesñevar
• Guillermo Ricardo Simari
• Lluís Godo
• Teresa Alsinet

NMR Workshop 2004 Conference Paper

A first approach to argument-based recommender systems based on defeasible logic programming

• Carlos Iván Chesñevar
• Ana Gabriela Maguitman
• Guillermo Ricardo Simari

Recommender systems have evolved in the last years as specialized tools to assist users in a plethora of computermediated tasks by providing guidelines or hints. Most recommender systems are aimed at facilitating access to relevant items, a situation particularly common when performing web-based tasks. At the same time, defeasible argumentation has evolved as a successful approach in AI to model commonsense qualitative reasoning, with applications in many areas, such as agent theory, knowledge engineering and legal reasoning. This paper presents a first approach towards the integration of web-based recommender systems with a defeasible argumentation framework. The final goal is to enhance practical reasoning capabilities of current recommender system technology by incorporating argument-based qualitative inference. K EYWORDS: Recommender systems, Defeasible Argumentation, Decision support systems, Practical reasoning

UAI Conference 2004 Conference Paper

A Logic Programming Framework for Possibilistic Argumentation with Vague Knowledge

• Carlos Iván Chesñevar
• Guillermo Ricardo Simari
• Teresa Alsinet
• Lluís Godo

Defeasible argumentation frameworks have evolved to become a sound setting to formalize commonsense, qualitative reasoning from incomplete and potentially inconsistent knowledge. Defeasible Logic Programming (DeLP) is a defeasible argumentation formalism based on an extension of logic programming. Although DeLP has been successfully integrated in a number of different real-world applications, DeLP cannot deal with explicit uncertainty, nor with vague knowledge, as defeasibility is directly encoded in the object language. This paper introduces P-DeLP, a new logic programming language that extends original DeLP capabilities for qualitative reasoning by incorporating the treatment of possibilistic uncertainty and fuzzy knowledge. Such features will be formalized on the basis of PGL, a possibilistic logic based on Godel fuzzy logic.

NMR Workshop 2004 Conference Paper

Actions, planning and defeasible reasoning

• Guillermo Ricardo Simari
• Alejandro Javier García
• Marcela Capobianco

The aim of this work is to study an argumentationbased formalism that an agent could use for constructing plans. Elsewhere, we have introduced a formalism for agents to represent knowledge about their environment in Defeasible Logic Programming, and a set of actions that they are capable of executing in order to change the environment where they are performing their tasks. We have also shown that action selection, when combined with a defeasible argumentation formalism, is more involved than expected. In this paper we will develop a novel way of using argumentation in the definition of actions and combining those actions to form plans. Since our interest here lies in exploring the important issues that need to be addressed, the main contribution will be to show meaningful examples where those issues are exhibited and not in improving current planning implementations. Therefore, we will use simple planning algorithms in an effort to reduce the complexity of the examples. Nevertheless, as the different ways of constructing plans introduce interesting details, we will be considering progression and regression planning.

NMR Workshop 2004 Conference Paper

Belief dynamics and defeasible argumentation in rational agents

• Marcelo A. Falappa
• Alejandro Javier García
• Guillermo Ricardo Simari

The BDI model provides what it is possibly one of the most promising architectures for the development of intelligent agents, and has become one of the most studied and well known in the literature. The basic BDI model needs to be complemented with two mechanisms: one for reasoning about intentions, and one for revising beliefs upon perception. In this work, we introduce a Revision Operator by a Set of Sentences which is a non-prioritized belief revision operator for changing the agent’s beliefs. These beliefs are contained in a Knowledge Base which is represented using the language of Defeasible Logic Programming. This formalism provides a framework for knowledge representation and reasoning about beliefs and intentions. The Knowledge Base is in fact a defeasible logic program and the belief revision operator will transform this program preserving as much information as possible taking into account for this transformation the reasons offered to justify the change in beliefs.

NMR Workshop 2004 Conference Paper

Preferential defeasibility: utility in defeasible logic programming

• Fernando A. Tohmé
• Guillermo Ricardo Simari

The development of Logic Programming and Defeasible Argumentation lead to Defeasible Logic Programming. Its core resides in the characterization of the warrant procedure. Defeasible Argumentation has provided a solid foundation over which the standard formalization of this procedure has been constructed. A key element in the warrant procedure is the criterion according to which two contradicting arguments are compared and eventually one of them deemed as defeating the other. The purely syntactic Specificity criterion has constituted the main choice in the design of the warrant procedure. Nevertheless, it seems unreasonable to limit the possibilities of comparison among arguments only to syntactic criteria. The justification of the methods of Defeasible Argumentation are largely pragmatic. Therefore, it seems sensible to expand the set of comparison criteria to incorporate other pragmatic reasons for choosing one argument over another. Decision Theory is the natural choice to model decision-makers. Clearly, as a discipline, it has characterized and introduced formal models in all kinds of pragmatic criteria used in actual choice situations. Here, we will present the framework of Preferential Defeasible Logic Programming. This framework extends the original comparison criteria of specificity redefining it by allowing different preferential values for activation sets. This extension leads to interesting results where the decision is taken considering not only specificity, but also the corresponding pragmatic relation of preferences.