References of "Pigozzi, Gabriella 40000533"
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See detailAGM Contraction and Revision of Rules
Boella, Guido; Pigozzi, Gabriella UL; van der Torre, Leon UL

in Journal of Logic, Language and Information (2016), 25(3), 273-297

In this paper we study AGM contraction and revision of rules using input/output logical theories. We replace propositional formulas in the AGM framework of theory change by pairs of propositional formulas ... [more ▼]

In this paper we study AGM contraction and revision of rules using input/output logical theories. We replace propositional formulas in the AGM framework of theory change by pairs of propositional formulas, representing the rule based character of theories, and we replace the classical consequence operator Cn by an input/output logic. The results in this paper suggest that, in general, results from belief base dynamics can be transferred to rule base dynamics, but that a similar transfer of AGM theory change to rule change is much more problematic. First, we generalise belief base contraction to rule base contraction, and show that two representation results of Hansson still hold for rule base contraction. Second, we show that the six so-called basic postulates of AGM contraction are consistent only for some input/output logics, but not for others. In particular, we show that the notorious recovery postulate can be satisfied only by basic output, but not by simple-minded output. Third, we show how AGM rule revision can be defined in terms of AGM rule contraction using the Levi identity. We highlight various topics for further research. [less ▲]

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See detailJudgment aggregation rules based on minimization.
Lang, J. UL; Pigozzi, Gabriella UL; Slavkovik, Marija UL et al

in Actes des Cinquièmes Journées Francophones Modèles Formel de l'Interaction (MFI 11) (2011, July 12), XIII

Many voting rules are based on some minimization principle. Likewise, in the field of logic-based knowledge representation and reasoning, many belief change or inconsistency handling operators also make ... [more ▼]

Many voting rules are based on some minimization principle. Likewise, in the field of logic-based knowledge representation and reasoning, many belief change or inconsistency handling operators also make use of minimization. Surprisingly, minimization has not played a major role in the field of judgment aggregation, in spite of its proximity to voting theory and logic-based knowledge representation and reasoning. Here we make a step in this direction and study six judgment aggregation rules; two of them, based on distances, have been previously defined; the other four are new, and all inspired both by voting theory and knowledge representation and reasoning. We study the inclusion relationships between these rules and address some of their social choice theoretic properties. [less ▲]

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See detailOn Judgment Aggregation in Abstract Argumentation
Caminada, Martin UL; Pigozzi, Gabriella UL

in Autonomous Agents & Multi-Agent Systems (2011), 22(1), 64102

Judgment aggregation is a field in which individuals are required to vote for or against a certain decision (the conclusion) while providing reasons for their choice. The reasons and the conclusion are ... [more ▼]

Judgment aggregation is a field in which individuals are required to vote for or against a certain decision (the conclusion) while providing reasons for their choice. The reasons and the conclusion are logically connected propositions. The problem is how a collective judgment on logically interconnected propositions can be defined from individual judgments on the same propositions. It turns out that, despite the fact that the individuals are logically consistent, the aggregation of their judgments may lead to an inconsistent group outcome, where the reasons do not support the conclusion. However, in this paper we claim that collective irrationality should not be the only worry of judgment aggregation. For example, judgment aggregation would not reject a consistent combination of reasons and conclusion that no member voted for. In our view this may not be a desirable solution. This motivates our research about when a social outcome is ‘compatible’ with the individuals’ judgments. The key notion that we want to capture is that any individual member has to be able to defend the collective decision. This is guaranteed when the group outcome is compatible with its members views. Judgment aggregation problems are usually studied using classical propositional logic. However, for our analysis we use an argumentation approach to judgment aggregation problems. Indeed the question of how individual evaluations can be combined into a collective one can also be addressed in abstract argumentation. We introduce three aggregation operators that satisfy the condition above, and we offer two definitions of compatibility. Not only does our proposal satisfy a good number of standard judgment aggregation postulates, but it also avoids the problem of individual members of a group having to become committed to a group judgment that is in conflict with their own individual positions. [less ▲]

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See detailA Satisficing Agreements Model
Boella, Guido UL; Pigozzi, Gabriella UL; Slavkovik, Marija UL et al

in Proceedings of the 13th International Workshop on Coordination, Organization, Institutions and Norms (COIN@WI-IAT) (2011)

Satisficing, the concept proposed by Herbert Simon, as an approach to reaching agreements is little explored. We propose a model for satisficing agreement reaching for an adaptive collaborative group of ... [more ▼]

Satisficing, the concept proposed by Herbert Simon, as an approach to reaching agreements is little explored. We propose a model for satisficing agreement reaching for an adaptive collaborative group of agents. The group consists of one human agent familiar with the problem and arbitrarily many artificial agents. Our model raises to the team level the recognition-primed decision model constructed in the field of cognitive decision-making by using social choice for reaching group opinions. [less ▲]

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See detailAggregation problems and models: what comes first?
Pigozzi, Gabriella UL

in Stadler, Friedrich (Ed.) The Present Situation in the Philosophy of Science (2010)

The aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on the same propositions has recently drawn attention in law, philosophy, economics ... [more ▼]

The aggregation of consistent individual judgments on logically interconnected propositions into a collective judgment on the same propositions has recently drawn attention in law, philosophy, economics and computer science. Despite the apparent simplicity of the problem, reasonable aggregation procedures, such as propositionwise majority voting, cannot ensure a consistent collective outcome. The literature on judgment aggregation has been influenced by earlier work in social choice theory. As preference aggregation investigated in social choice theory, judgment aggregation studies aggregation functions under specific conditions. These are derived from properties of the preference aggregation realm. In this paper we argue that judgment aggregation problems are intrinsically different from preference aggregation ones. Thus, imposing exogenous models and properties is detrimental to a deep understanding of the specificity of judgment aggregation. [less ▲]

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See detailNormative Multiagent Systems: Guest Editors' Introduction
Boella, Guido; Pigozzi, Gabriella UL; Singh, Munindar P. et al

in Logic Journal of the IGPL (2010), 18(1), 13

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See detailIndividual Opinions-Based Judgment Aggregation Procedures
Benamara, Farah; Kaci, Souhila; Pigozzi, Gabriella UL

in Modeling Decisions for Artificial Intelligence (2010)

Judgment aggregation is a recent formal discipline that studies how to aggregate individual judgments on logically connected propositions to form collective decisions on the same propositions. Despite the ... [more ▼]

Judgment aggregation is a recent formal discipline that studies how to aggregate individual judgments on logically connected propositions to form collective decisions on the same propositions. Despite the apparent simplicity of the problem, the aggregation of individual judgments can result in an inconsistent outcome. This seriously troubles this research field. Expert panels, legal courts, boards, and councils are only some examples of group decision situations that confront themselves with such aggregation problems. So far, the existing framework and procedures considered in the literature are idealized. Our goal is to enrich standard judgment aggregation by allowing the individuals to agree or disagree on the decision rule. Moreover, the group members have the possibility to abstain or express neutral judgments. This provides a more realistic framework and, at the same time, consents the definition of an aggregation procedure that escapes the inconsistent group outcome. [less ▲]

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See detailGroup Intentions are Social Choice with Commitment
Boella, Guido UL; Pigozzi, Gabriella UL; Slavkovik, Marija UL et al

in Pre-Procs. of the 11th International Workshop on Coordination, Optimization, Institution and Norms in Multiagent Systems (COIN@MALLOW'10) (2010)

An agent intends g if it has chosen to pursue goal g an is committed to pursuing g . How do groups decide on a common goal? Social epistemology offers two views on collective attitudes: according to the ... [more ▼]

An agent intends g if it has chosen to pursue goal g an is committed to pursuing g . How do groups decide on a common goal? Social epistemology offers two views on collective attitudes: according to the summative approach, a group has attitude p if all or most of the group members have the attitude p; according to the non-summative approach, for a group to have attitude p it is required that the members together agree that they have attitude p. The summative approach is used extensively in multi-agent systems. We propose a formalization of non-summative group intentions, using social choice to determine the group goals. We use judgment aggregation as a decision-making mechanism and a multi-modal multi-agent logic to represent the collective attitudes, as well as the commitment and revision strategies for the groups intentions. [less ▲]

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See detailReliable Methods of Judgement Aggregation
Hartmann, Stephan; Pigozzi, Gabriella UL; Sprenger, Jan

in Journal of Logic & Computation (2010), 20(2), 603617

The aggregation of consistent individual judgements on logically interconnected propositions into a collective judgement on the same propositions has recently drawn much attention. Seemingly reasonable ... [more ▼]

The aggregation of consistent individual judgements on logically interconnected propositions into a collective judgement on the same propositions has recently drawn much attention. Seemingly reasonable aggregation procedures, such as propositionwise majority voting, cannot ensure an equally consistent collective conclusion. The literature on judgement aggregation refers to such a problem as the discursive dilemma. In this article we assume that the decision which the group is trying to reach is factually right or wrong. Hence, we address the question of how good various approaches are at selecting the right conclusion. We focus on two approaches: distance-based procedures and a Bayesian analysis. They correspond to group-internal and group external decision making, respectively. We compare those methods in a probabilistic model whose assumptions are subsequently relaxed. Our findings have two general implications for judgement aggregation problems: first, in a voting procedure, reasons should carry higher weight than the conclusion, and second, considering members of an advisory board to be highly competent is a better strategy than discounting their advice. [less ▲]

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See detailFive guidelines for normative multiagent systems
Boella, Guido UL; Pigozzi, Gabriella UL; van der Torre, Leon UL

in Proceedings of JURIX 2009 - The 22nd International Conference on Legal Knowledge and Information Systems (2009, December)

n this paper we introduce and discuss five guidelines for the use of normative systems in computer science. We adopt a multiagent systems perspective, because norms are used to coordinate, organize, guide ... [more ▼]

n this paper we introduce and discuss five guidelines for the use of normative systems in computer science. We adopt a multiagent systems perspective, because norms are used to coordinate, organize, guide, regulate or control interaction among distributed autonomous systems. They are derived from the computer science literature. From the so-called ‘normchange’ definition of the first workshop on normative multiagent systems in 2005 we derive the guidelines to motivate which definition of normative multiagent system is used, to make explicit why norms are a kind of (soft) constraints deserving special analysis, and to explain why and how norms can be changed at runtime. From the so-called ‘mechanism design’ definition of the second workshop on normative multiagent systems in 2007 we derive the guidelines to discuss the use and role of norms as a mechanism in a game-theoretic setting, and to clarify the role of norms in the multiagent system. [less ▲]

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See detailWhite Manipulation in Judgment Aggregation
Grossi, Davide; Pigozzi, Gabriella UL; Slavkovik, Marija UL

Scientific Conference (2009)

Distributive systems consisting of autonomous and intelligent components need to be able to reason and make decisions based on the information these components share. Judgment aggregation investigates how ... [more ▼]

Distributive systems consisting of autonomous and intelligent components need to be able to reason and make decisions based on the information these components share. Judgment aggregation investigates how individual judgments on logically connected propositions can be aggregated into a collective judgment on the same propositions. It is the case that seemingly reasonable aggregation procedures may force the group to hold an inconsistent judgment set. What happens when the agents realize that the group outcome will be inconsistent? We claim that, in order to avoid an untenable collective outcome, individuals may prefer to declare a non-truthful, less preferred judgment set. Thus, the prospect of an individual trying to manipulate the social outcome by submitting an insincere judgment set is turned from being an undesirable to a “virtuous” (or white) manipulation. We define white manipulation and present the initial study of it as a coordinated action of the whole group. [less ▲]

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See detailA complete conclusion-based procedure for judgment aggregation
Pigozzi, Gabriella UL; Slavkovik, Marija UL; van der Torre, Leon UL

in Proceedings of the First International Conference on Algorithmic Decision Theory (ADT) (2009)

Judgment aggregation is a formal theory reasoning about how a group of agents can aggregate individual judgments on connected propositions into a collective judgment on the same propositions. Three ... [more ▼]

Judgment aggregation is a formal theory reasoning about how a group of agents can aggregate individual judgments on connected propositions into a collective judgment on the same propositions. Three procedures for successfully aggregating judgments sets are: premise-based procedure, conclusion-based procedure and distance-based merging. The conclusion-based procedure has been little investigated because it provides a way to aggregate the conclusions, but not the premises, thus it outputs an incomplete judgment set. The goal of this paper is to present a conclusion-based procedure outputting complete judgment sets. [less ▲]

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See detailNormative framework for normative system change
Boella, Guido UL; Pigozzi, Gabriella UL; van der Torre, Leon UL

in Normative framework for normative system change (2009)

Normative systems in a multiagent system must be able to evolve over time, for example due to actions creating or removing norms in the system. The only formal framework to evaluate and classify normative ... [more ▼]

Normative systems in a multiagent system must be able to evolve over time, for example due to actions creating or removing norms in the system. The only formal framework to evaluate and classify normative system change methods is the so-called AGM framework of theory change, which has originally been developed as a framework to describe and classify both belief and normative system change. However, it has been used for belief change only, since the beliefs or norms are represented as propositional formulas. We therefore propose, as a normative framework for normative system change, to replace propositional formulas in the AGM framework of theory change by pairs of propositional formulas, representing the rule based character of norms, and to add several principles from the input/output logic framework. In this new framework, we show that some of the AGM properties cannot be expressed, and other properties are consistent only for some logics, but not for others. [less ▲]

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See detailThe role of goals in belief selection
Boella, Guido UL; Pereira, Célia Da Costa UL; Pigozzi, Gabriella UL et al

in Logic Journal of the IGPL (2009)

In this paper we consider the relation between beliefs and goals in agent theory. Beliefs play three roles in reasoning about goals: they play a role in the generation of unconditional desires from ... [more ▼]

In this paper we consider the relation between beliefs and goals in agent theory. Beliefs play three roles in reasoning about goals: they play a role in the generation of unconditional desires from conditional ones, they play a role in adoption of desires as goals, and they play a role in the selection of plans to achieve goals. In this paper we consider the role of goals in reasoning about beliefs. Though we assume that goals do not play a role in the belief generation problem, we argue that they play a role in the belief selection problem. We show the rationality of the use of goals in belief selection, in the sense that there are cases in which agents that take their goals into account in selecting a belief set from a set of alternatives outperform agents that do not do so. We also formally distinguish between the rational role of goals in belief selection and irrational wishful thinking. [less ▲]

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See detailNormative systems in computer science. Ten guidelines for normative multiagent systems
Boella, Guido UL; Pigozzi, Gabriella UL; van der Torre, Leon UL

in Normative Multi-Agent Systems, Dagstuhl Seminar Proceedings 09121 (2009)

In this paper we introduce and discuss ten guidelines for the use of normative systems in computer science. We adopt a multiagent sys- tems perspective, because norms are used to coordinate, organize ... [more ▼]

In this paper we introduce and discuss ten guidelines for the use of normative systems in computer science. We adopt a multiagent sys- tems perspective, because norms are used to coordinate, organize, guide, regulate or control interaction among distributed autonomous systems. The first six guidelines are derived from the computer science literature. From the so-called ‘normchange’ definition of the first workshop on nor- mative multiagent systems in 2005 we derive the guidelines to motivate which definition of normative multiagent system is used, to make explicit why norms are a kind of (soft) constraints deserving special analysis, and to explain why and how norms can be changed at runtime. From the so-called ‘mechanism design’ definition of the second workshop on nor- mative multiagent systems in 2007 we derive the guidelines to discuss the use and role of norms as a mechanism in a game-theoretic setting, clarify the role of norms in the multiagent system, and to relate the no- tion of “norm” to the legal, social, or moral literature. The remaining four guidelines follow from the philosophical literature: use norms also to resolve dilemmas, and in general to coordinate, organize, guide, regulate or control interaction among agents, distinguish norms from obligations, prohibitions and permissions, use the deontic paradoxes only to illustrate the normative multiagent system, and consider regulative norms in rela- tion to other kinds of norms and other social-cognitive computer science concepts. [less ▲]

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See detailFrom belief change to norm change
Pigozzi, Gabriella UL; van der Torre, Leon UL

in Prague International Colloquium: Logic of change, change of logic, LOCCOL'08 (2008)

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See detailDesirable Tie-breaking Rules in Collective Decision Making
Pigozzi, Gabriella UL; Slavkovik, Marija UL; van der Torre, Leon UL

in Annales du Lamsade, Proceedings of the DIMACS-LAMSADE Workshop on Algorithmic Decision Theory (2008)

Judgment aggregation (JA) studies how to aggregate individual judgments to form collective decisions. Examples are expert panels, legal courts, boards, and councils. The problems investigated in this new ... [more ▼]

Judgment aggregation (JA) studies how to aggregate individual judgments to form collective decisions. Examples are expert panels, legal courts, boards, and councils. The problems investigated in this new field are relevant and common to many situations. Nevertheless, the existing procedures are idealized and, likewise the related problems of preference aggregation in social choice theory, the field is plagued by impossibility theorems. In this paper, we extend standard JA in order to offer a more realistic framework and to escape the impossibility results. We propose to distinguish between abstainers and neutral judgment as well as to model the notion of confidence a group member may have in the decision rule by assigning to each criterion a normalized weight. We then show how this new framework may help us to avoid indecision in most cases. [less ▲]

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See detailConclusion-based procedure for judgment aggregation satisfying premise independence
Pigozzi, Gabriella UL; Slavkovik, Marija UL; van der Torre, Leon UL

in Proceedings of the Eighth International Conference on Logic and the Foundations of Game and Decision Theory, LOFT 2008 (2008)

Judgment aggregation is a formal theory reasoning about how a group of agents can aggregate individual judgments on connected propositions into a collective judgment on the same propositions. Three ... [more ▼]

Judgment aggregation is a formal theory reasoning about how a group of agents can aggregate individual judgments on connected propositions into a collective judgment on the same propositions. Three procedures for successfully aggregating judgments sets are: premise-based procedure, conclusion-based procedure and distance-based merging. The conclusion-based procedure has been little investigated because it pro- vides a way to aggregate the conclusions, but not the premises, thus it outputs an incomplete judgment set. The goal of this paper is to present a conclusion-based procedure outputting complete judgment sets. [less ▲]

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See detailIndependence in judgment aggregation
Pigozzi, Gabriella UL; Slavkovik, Marija UL; van der Torre, Leon UL

in Proceedings of the Ninth International Meeting of the Society for Social Choice and Welfare, SCW'08 (2008)

One of the better studied properties for operators in judgment aggregation is independence, which essentially dictates that the collective judgment on one issue should not depend on the individual ... [more ▼]

One of the better studied properties for operators in judgment aggregation is independence, which essentially dictates that the collective judgment on one issue should not depend on the individual judgments given on some other issue(s) in the same agenda. Independence is a desirable property for various reasons, but unfortunately it is too strong, as, together with mild additional conditions, it implies dictatorship. We propose here a weakening of independence, named agenda separability and show that this property is discriminant, i.e., some judgment aggregation rules satisfy it, others do not. [less ▲]

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See detailWhat You should Believe
Boella, Guido UL; Pereira, Célia Da Costa UL; Pigozzi, Gabriella UL et al

in Proceedings of The 19th Belgian-Dutch Conference on Artificial Intelligence (BNAIC 2007) (2007)

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