13 research outputs found
The Strategy-Proofness Landscape of Merging
Merging operators aim at defining the beliefs/goals of a group of agents from
the beliefs/goals of each member of the group. Whenever an agent of the group
has preferences over the possible results of the merging process (i.e., the
possible merged bases), she can try to rig the merging process by lying on her
true beliefs/goals if this leads to better merged base according to her point
of view. Obviously, strategy-proof operators are highly desirable in order to
guarantee equity among agents even when some of them are not sincere. In this
paper, we draw the strategy-proof landscape for many merging operators from the
literature, including model-based ones and formula-based ones. Both the general
case and several restrictions on the merging process are considered
Trust-sensitive belief revision
Belief revision is concerned with incorporating new information into a pre-existing set of beliefs. When the new information comes from another agent, we must first determine if that agent should be trusted. In this paper, we define trust as a pre-processing step before revision. We emphasize that trust in an agent is often restricted to a particular domain of expertise. We demonstrate that this form of trust can be captured by associating a state partition with each agent, then relativizing all reports to this partition before revising. We position the resulting family of trust-sensitive revision operators within the class of selective revision operators of Fermé and Hansson, and we examine its properties. In particular, we show how trust-sensitive revision is manipulable, in the sense that agents can sometimes have incentive to pass on misleading information. When multiple reporting agents are involved, we use a distance function over states to represent differing degrees of trust; this ensures that the most trusted reports will be believed
Trust as a precursor to belief revision
Belief revision is concerned with incorporating new information into a pre-existing set of beliefs. When the new information comes from another agent, we must first determine if that agent should be trusted. In this paper, we define trust as a pre-processing step before revision. We emphasize that trust in an agent is often restricted to a particular domain of expertise. We demonstrate that this form of trust can be captured by associating a state partition with each agent, then relativizing all reports to this partition before revising. We position the resulting family of trust-sensitive revision operators within the class of selective revision operators of Ferme and Hansson, and we prove a representation result that characterizes the class of trust-sensitive revision operators in terms of a set of postulates. We also show that trust-sensitive revision is manipulable, in the sense that agents can sometimes have incentive to pass on misleading information
Belief Integration and Source Reliability Assessment
Merging beliefs requires the plausibility of the sources of the information to be merged. They are typically assumed equally reliable when nothing suggests otherwise. A recent line of research has spun from the idea of deriving this information from the revision process itself. In particular, the history of previous revisions and previous merging examples provide information for performing subsequent merging operations.
Yet, no examples or previous revisions may be available. In spite of the apparent lack of information, something can still be inferred by a try-and-check approach: a relative reliability ordering is assumed, the sources are integrated according to it and the result is compared with the original information. The final check may contradict the original ordering, like when the result of merging implies the negation of a formula coming from a source initially assumed reliable, or it implies a formula coming from a source assumed unreliable. In such cases, the reliability ordering assumed in the first place can be excluded from consideration.
Such a scenario is proved real under the classifications of source reliability and definitions of belief integration considered in this article: sources divided in two, three or multiple reliability classes; integration is mostly by maximal consistent subsets but also weighted distance is considered. Other results mainly concern the integration by maximal consistent subsets and partitions of two and three reliability classes
Multi-Winner Voting with Approval Preferences
Approval-based committee (ABC) rules are voting rules that output a
fixed-size subset of candidates, a so-called committee. ABC rules select
committees based on dichotomous preferences, i.e., a voter either approves or
disapproves a candidate. This simple type of preferences makes ABC rules widely
suitable for practical use. In this book, we summarize the current
understanding of ABC rules from the viewpoint of computational social choice.
The main focus is on axiomatic analysis, algorithmic results, and relevant
applications.Comment: This is a draft of the upcoming book "Multi-Winner Voting with
Approval Preferences
Multi-Winner Voting with Approval Preferences
From fundamental concepts and results to recent advances in computational social choice, this open access book provides a thorough and in-depth look at multi-winner voting based on approval preferences. The main focus is on axiomatic analysis, algorithmic results and several applications that are relevant in artificial intelligence, computer science and elections of any kind. What is the best way to select a set of candidates for a shortlist, for an executive committee, or for product recommendations? Multi-winner voting is the process of selecting a fixed-size set of candidates based on the preferences expressed by the voters. A wide variety of decision processes in settings ranging from politics (parliamentary elections) to the design of modern computer applications (collaborative filtering, dynamic Q&A platforms, diversity in search results, etc.) share the problem of identifying a representative subset of alternatives. The study of multi-winner voting provides the principled analysis of this task. Approval-based committee voting rules (in short: ABC rules) are multi-winner voting rules particularly suitable for practical use. Their usability is founded on the straightforward form in which the voters can express preferences: voters simply have to differentiate between approved and disapproved candidates. Proposals for ABC rules are numerous, some dating back to the late 19th century while others have been introduced only very recently. This book explains and discusses these rules, highlighting their individual strengths and weaknesses. With the help of this book, the reader will be able to choose a suitable ABC voting rule in a principled fashion, participate in, and be up to date with the ongoing research on this topic
Complex negotiations in multi-agent systems
Los sistemas multi-agente (SMA) son sistemas distribuidos donde entidades autónomas llamadas
agentes, ya sean humanos o software, persiguen sus propios objetivos. El paradigma de SMA ha
sido propuesto como la aproximación de modelo apropiada para aplicaciones como el comercio
electrónico, los sistemas multi-robot, aplicaciones de seguridad, etc. En la comunidad de SMA, la
visión de sistemas multi-agente abiertos, donde agentes heterogéneos pueden entrar y salir del
sistema dinámicamente, ha cobrado fuerza como paradigma de modelado debido a su relación
conceptual con tecnologías como la Web, la computación grid, y las organizaciones virtuales.
Debido a la heterogeneidad de los agentes, y al hecho de dirigirse por sus propios objetivos, el
conflicto es un fenómeno candidato a aparecer en los sistemas multi-agente.
En los últimos años, el término tecnologías del acuerdo ha sido usado para referirse a todos aquellos
mecanismos que, directa o indirectamente, promueven la resolución de conflictos en sistemas
computacionales como los sistemas multi-agente. Entre las tecnologías del acuerdo, la negociación
automática ha sido propuesta como uno de los mecanismos clave en la resolución de conflictos
debido a su uso análogo en la resolución de conflictos entre humanos. La negociación automática
consiste en el intercambio automático de propuestas llevado a cabo por agentes software en nombre
de sus usuarios. El objetivo final es conseguir un acuerdo con todas las partes involucradas.
Pese a haber sido estudiada por la Inteligencia Artificial durante años, distintos problemas todavía
no han sido resueltos por la comunidad científica todavía. El principal objetivo de esta tesis es
proponer modelos de negociación para escenarios complejos donde la complejidad deriva de (1) las
limitaciones computacionales o (ii) la necesidad de representar las preferencias de múltiples
individuos. En la primera parte de esta tesis proponemos un modelo de negociación bilateral para el
problema deSánchez Anguix, V. (2013). Complex negotiations in multi-agent systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/21570Palanci