scholarly journals Compact preference representation and Boolean games

2008 ◽  
Vol 18 (1) ◽  
pp. 1-35 ◽  
Author(s):  
Elise Bonzon ◽  
Marie-Christine Lagasquie-Schiex ◽  
Jérôme Lang ◽  
Bruno Zanuttini
Keyword(s):  
Preference Representation ◽  
Boolean Games

Compact Preference Representation for Boolean Games

2006 ◽  
pp. 41-50 ◽  
Author(s):  
Elise Bonzon ◽  
Marie-Christine Lagasquie-Schiex ◽  
Jérôme Lang
Keyword(s):  
Preference Representation ◽  
Boolean Games

Compact Preference Representation for Boolean Games

2006 ◽  
pp. 41-50 ◽  
Author(s):  
Elise Bonzon ◽  
Marie-Christine Lagasquie-Schiex ◽  
Jérôme Lang
Keyword(s):  
Preference Representation ◽  
Boolean Games

scholarly journals Expressiveness and Nash Equilibrium in Iterated Boolean Games

2021 ◽  
Vol 22 (2) ◽  
pp. 1-38
Author(s):  
Julian Gutierrez ◽  
Paul Harrenstein ◽  
Giuseppe Perelli ◽  
Michael Wooldridge
Keyword(s):  
Nash Equilibrium ◽  
Nash Equilibria ◽  
Infinite Sequence ◽  
Multi Agent Systems ◽  
Temporal Logics ◽  
Agent Systems ◽  
Temporal Properties ◽  
Multi Agent ◽  
Game Theoretic ◽  
Boolean Games

We define and investigate a novel notion of expressiveness for temporal logics that is based on game theoretic equilibria of multi-agent systems. We use iterated Boolean games as our abstract model of multi-agent systems [Gutierrez et al. 2013, 2015a]. In such a game, each agent  has a goal  , represented using (a fragment of) Linear Temporal Logic ( ) . The goal  captures agent  ’s preferences, in the sense that the models of  represent system behaviours that would satisfy  . Each player controls a subset of Boolean variables , and at each round in the game, player is at liberty to choose values for variables in any way that she sees fit. Play continues for an infinite sequence of rounds, and so as players act they collectively trace out a model for , which for every player will either satisfy or fail to satisfy their goal. Players are assumed to act strategically, taking into account the goals of other players, in an attempt to bring about computations satisfying their goal. In this setting, we apply the standard game-theoretic concept of (pure) Nash equilibria. The (possibly empty) set of Nash equilibria of an iterated Boolean game can be understood as inducing a set of computations, each computation representing one way the system could evolve if players chose strategies that together constitute a Nash equilibrium. Such a set of equilibrium computations expresses a temporal property—which may or may not be expressible within a particular fragment. The new notion of expressiveness that we formally define and investigate is then as follows: What temporal properties are characterised by the Nash equilibria of games in which agent goals are expressed in specific fragments of  ? We formally define and investigate this notion of expressiveness for a range of fragments. For example, a very natural question is the following: Suppose we have an iterated Boolean game in which every goal is represented using a particular fragment of : is it then always the case that the equilibria of the game can be characterised within ? We show that this is not true in general.

scholarly journals Dependencies between players in Boolean games

2009 ◽  
Vol 50 (6) ◽  
pp. 899-914 ◽  
Author(s):  
Elise Bonzon ◽  
Marie-Christine Lagasquie-Schiex ◽  
Jérôme Lang
Keyword(s):  
Boolean Games

Personalisation in Highly Dynamic Grid Services Environments

2009 ◽  
pp. 284-313
Author(s):  
Edgar Jembere ◽  
Matthew O. Adigun ◽  
Sibusiso S. Xulu
Keyword(s):  
User Preferences ◽  
User Preference ◽  
Grid Services ◽  
Context Aware Computing ◽  
Preference Representation ◽  
Use Of Services ◽  
Order Preference ◽  
Computing Environments ◽  
Preference Models ◽  
Intuitive Interpretation

Human Computer Interaction (HCI) challenges in highly dynamic computing environments can be solved by tailoring the access and use of services to user preferences. In this era of emerging standards for open and collaborative computing environments, the major challenge that is being addressed in this chapter is how personalisation information can be managed in order to support cross-service personalisation. The authors’ investigation of state of the art work in personalisation and context-aware computing found that user preferences are assumed to be static across different context descriptions whilst in reality some user preferences are transient and vary with changes in context. Further more, the assumed preference models do not give an intuitive interpretation of a preference and lack user expressiveness. This chapter presents a user preference model for dynamic computing environments, based on an intuitive quantitative preference measure and a strict partial order preference representation, to address these issues. The authors present an approach for mining context-based user preferences and its evaluation in a synthetic m-commerce environment. This chapter also shows how the data needed for mining context-based preferences is gathered and managed in a Grid infrastructure for mobile devices.

Effectivity functions and efficient coalitions in Boolean games

Synthese ◽  
2012 ◽  
Vol 187 (S1) ◽  
pp. 73-103 ◽  
Author(s):  
Elise Bonzon ◽  
Marie-Christine Lagasquie-Schiex ◽  
Jérôme Lang
Keyword(s):  
Effectivity Functions ◽  
Boolean Games

Regulation of game result for n ‐person random evolutionary Boolean games

2019 ◽  
Vol 22 (6) ◽  
pp. 2353-2362 ◽  
Author(s):  
Xueying Ding ◽  
Haitao Li ◽  
Fuad E. Alsaadi
Keyword(s):  
Boolean Games

Learning-Based Preference Modeling in Engineering Design Decision-Making

1999 ◽  
Vol 123 (2) ◽  
pp. 191-198 ◽  
Author(s):  
Jie Wan ◽  
Sundar Krishnamurty
Keyword(s):  
Engineering Design ◽  
Deductive Reasoning ◽  
Integrated Approach ◽  
Design Decision ◽  
Learning Method ◽  
Preference Modeling ◽  
Modeling Process ◽  
Preference Representation ◽  
Elicitation Process ◽  
Effective Integration

Focusing on the efforts towards a consistent preference representation in decision based engineering design, this paper presents a learning-based comparison and preference modeling process. Through effective integration of a deductive reasoning-based on designer’s outcome ranking in a lottery questions-based elicitation process, this work offers a reliable framework for formulating utility functions that reflect designer’s priorities accurately and consistently. It is expected that this integrated approach will reduce designer’s cognitive burden, and lead to accurate and consistent preference representation. Salient features of this approach include a linear programming based dynamic preference learning method and a logical analysis of preference inconsistencies. The development of this method and its utilization in engineering design are presented in the context of a mechanism design problem and the results are discussed.

Preference Representation and the Limits of Reform: The 1976 Democratic Convention

1982 ◽  
Vol 44 (1) ◽  
pp. 201-211 ◽  
Author(s):  
David C. Paris ◽  
Richard D. Shingles
Keyword(s):  
Preference Representation
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