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Efficiency and envyfreeness in fair division of indivisible goods: Logical representation and complexity
 In Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI2005
, 2005
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Preference Handling in Combinatorial Domains: From AI to Social Choice
"... In both individual and collective decision making, the space of alternatives from which the agent (or the group of agents) has to choose often has a combinatorial (or multiattribute) structure. We give an introduction to preference handling in combinatorial domains in the context of collective deci ..."
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Cited by 24 (12 self)
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In both individual and collective decision making, the space of alternatives from which the agent (or the group of agents) has to choose often has a combinatorial (or multiattribute) structure. We give an introduction to preference handling in combinatorial domains in the context of collective decision making, and show that the considerable body of work on preference representation and elicitation that AI researchers have been working on for several years is particularly relevant. After giving an overview of languages for compact representation of preferences, we discuss problems in voting in combinatorial domains, and then focus on multiagent resource allocation and fair division. These issues belong to a larger field, known as computational social choice, that brings together ideas from AI and social choice theory, to investigate mechanisms for collective decision making from a computational point of view. We conclude by briefly describing some of the other research topics studied in computational social choice.
Dependencies between players in Boolean games
 In Proc. ECSQARU ’07, volume 4724 of LNCS
, 2007
"... Boolean games are a logical setting for representing static games in a succinct way, taking advantage of the expressive power and succinctness of propositional logic. A Boolean game consists of a set of players, each of them controlling a set of propositional variables and having a specific goal ex ..."
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Cited by 21 (1 self)
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Boolean games are a logical setting for representing static games in a succinct way, taking advantage of the expressive power and succinctness of propositional logic. A Boolean game consists of a set of players, each of them controlling a set of propositional variables and having a specific goal expressed by a propositional formula, or more generally a specification of the player’s preference relation in some logical language for compact preference representation, such as prioritized goals. There is a lot of graphical structure hidden in a Boolean game: the satisfaction of each player’s goal depends on players whose actions have an influence on her goals. Exploiting this dependency structure facilitates the computation of pure Nash equilibria, by partly decomposing a game into several subgames that are only loosely related. Key words: Game theory, compact preference representation, problem decomposition 1
Preference Aggregation with Graphical Utility Models
"... This paper deals with preference representation and aggregation in the context of multiattribute utility theory. We consider a set of alternatives having a combinatorial structure. We assume that preferences are compactly represented by graphical utility models derived from generalized additive deco ..."
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Cited by 12 (2 self)
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This paper deals with preference representation and aggregation in the context of multiattribute utility theory. We consider a set of alternatives having a combinatorial structure. We assume that preferences are compactly represented by graphical utility models derived from generalized additive decomposable (GAI) utility functions. Such functions enable to model interactions between attributes while preserving some decomposability property. We address the problem of finding a compromise solution from several GAI utilities representing different points of view on the alternatives. This scheme can be applied both to multicriteria decision problems and to collective decision making problems over combinatorial domains. We propose a procedure using graphical models for the fast determination of a Paretooptimal solution achieving a good compromise between the conflicting utilities. The procedure relies on a ranking algorithm enumerating solutions according to the sum of all the GAI utilities until a boundary condition is reached. Numerical experiments are provided to highlight the practical efficiency of our procedure.
Description logics for multiissue bilateral negotiation with incomplete information
 In Proceedings AAAI2007
, 2007
"... We propose a framework for multiissue bilateral negotiation, where issues are expressed and related to each other via Description Logics. Agents ’ goals are expressed through (complex) concepts, and the worth of goals as weights over concepts. We adopt a very general setting with incomplete inf ..."
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Cited by 10 (9 self)
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We propose a framework for multiissue bilateral negotiation, where issues are expressed and related to each other via Description Logics. Agents ’ goals are expressed through (complex) concepts, and the worth of goals as weights over concepts. We adopt a very general setting with incomplete information by letting agents keep both goals and worths of goals as private information. We introduce a negotiation protocol for such a setting, and discuss different possible strategies that agents can adopt during the negotiation process. We show that such a protocol converges, if the Description Logic used enjoys the finite implicants property.
Logicbased automated multiissue bilateral negotiation in peertopeer emarketplaces
 JOURNAL
, 2008
"... We present a novel logicbased framework to automate multiissue bilateral negotiation in ecommerce settings. The approach exploits logic as communication language among agents, and optimization techniques in order to find Paretoefficient agreements. We introduce P(N), a propositional logic exten ..."
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Cited by 7 (5 self)
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We present a novel logicbased framework to automate multiissue bilateral negotiation in ecommerce settings. The approach exploits logic as communication language among agents, and optimization techniques in order to find Paretoefficient agreements. We introduce P(N), a propositional logic extended with concrete domains, which allows one to model relations among issues (both numerical and nonnumerical ones) via logical entailment, differently from wellknown approaches that describe issues as uncorrelated. Through P(N) it is possible to represent buyer’s request, seller’s supply and their respective preferences as formulas endowed with a formal semantics, e.g., “if I spend more than 30000 e for a sedan then I want more than a twoyears warranty and a GPS system included”. We mix logic and utility theory in order to express preferences in a qualitative and quantitative way. We illustrate the theoretical framework, the logical language, the oneshot negotiation protocol we adopt, and show we are able to compute Paretoefficient outcomes, using a mediator to solve an optimization problem. We prove the computational adequacy of our method by studying the complexity of the problem of finding Paretoefficient solutions in our setting.
Winner determination in combinatorial auctions with logicbased bidding languages. In
 AAMAS 2008: 7th International Conference on Autonomous Agents and MultiAgent Systems: Proceedings: Volume
, 2008
"... ABSTRACT We propose the use of logicbased preference representation languages based on weighted propositional formulas for specifying bids in a combinatorial auction. We then develop several heuristics for a branchandbound search algorithm for determining the winning bids in this framework and r ..."
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Cited by 5 (3 self)
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ABSTRACT We propose the use of logicbased preference representation languages based on weighted propositional formulas for specifying bids in a combinatorial auction. We then develop several heuristics for a branchandbound search algorithm for determining the winning bids in this framework and report on their empirical performance. The logicbased approach is attractive due to its high degree of flexibility in designing a range of different bidding languages within a single conceptual framework.
Weighted Description Logics Preference Formulas for Multiattribute Negotiation
"... Abstract. We propose a framework to compute the utility of an agreement w.r.t. a preference set in a negotiation process. In particular, we refer to preferences expressed as weighted formulas in a decidable fragment of Firstorder Logic and agreements expressed as a formula. We ground our framework ..."
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Cited by 5 (2 self)
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Abstract. We propose a framework to compute the utility of an agreement w.r.t. a preference set in a negotiation process. In particular, we refer to preferences expressed as weighted formulas in a decidable fragment of Firstorder Logic and agreements expressed as a formula. We ground our framework in Description Logics (DL) endowed with disjunction, to be compliant with Semantic Web technologies. A logic based approach to preference representation allows, when a background knowledge base is exploited, to relax the often unrealistic assumption of additive independence among attributes. We provide suitable definitions of the problem and present algorithms to compute utility in our setting. We also validate our approach through an experimental evaluation. 1
Logicbased preference languages with intermediate complexity
 in: Proceedings of the 4th Multidisciplinary Workshop on Advances in Preference Handling (MPREF2008), (AAAI
, 2008
"... Logicbased preference representation languages are used to represent utility functions in combinatorial auctions, and can also be used for voting. A canonical problem in this context is, given a set of propositional formulas with associated weights, to find an assignment1 that maximizes the sum of ..."
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Cited by 3 (3 self)
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Logicbased preference representation languages are used to represent utility functions in combinatorial auctions, and can also be used for voting. A canonical problem in this context is, given a set of propositional formulas with associated weights, to find an assignment1 that maximizes the sum of those weights which are associated to satisfied formulas. The general case is intractable, and natural restrictions of the languages tend either to leave the complexity unchanged or to reduce it to triviality. After proposing a revision of the decision problem considered in existing research, we use a new approach to find languages with Pcomplete maximization problem.
Preference modeling by weighted goals with max aggregation, in:
 Proc. 11th International Conference on Principles of Knowledge Representation and Reasoning (KR2008),
, 2008
"... Abstract Logicbased preference representation languages are promising for expressing preferences over combinatorial domains. Sets of weighted formulas, called goalbases, can be used to define several such languages. How goalbases are translated into utility functionsthat is, by what aggregation f ..."
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Cited by 3 (3 self)
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Abstract Logicbased preference representation languages are promising for expressing preferences over combinatorial domains. Sets of weighted formulas, called goalbases, can be used to define several such languages. How goalbases are translated into utility functionsthat is, by what aggregation function this is doneis a crucial component of this type of language. In this paper, we consider the properties of several goalbase languages which use max as their aggregation function. In particular, we examine the expressivity, succinctness and complexity of such languages.