An Efficient Protocol for Negotiation over Combinatorial Domains with Incomplete Information

We study the problem of agent-based negotiation in combinatorial domains. It is difficult to reach optimal agreements in bilateral or multi-lateral negotiations when the agents' preferences for the possible alternatives are not common knowledge. Self-interested agents often end up negotiating inefficient agreements in such situations. In this paper, we present a protocol for negotiation in combinatorial domains which can lead rational agents to reach optimal agreements under incomplete information setting. Our proposed protocol enables the negotiating agents to identify efficient solutions using distributed search that visits only a small subspace of the whole outcome space. Moreover, the proposed protocol is sufficiently general that it is applicable to most preference representation models in combinatorial domains. We also present results of experiments that demonstrate the feasibility and computational efficiency of our approach

Ordering based decision making: a survey

Decision making is the crucial step in many real applications such as organization management, financial planning, products evaluation and recommendation. Rational decision making is to select an alternative from a set of different ones which has the best utility (i.e., maximally satisfies given criteria, objectives, or preferences). In many cases, decision making is to order alternatives and select one or a few among the top of the ranking. Orderings provide a natural and effective way for representing indeterminate situations which are pervasive in commonsense reasoning. Ordering based decision making is then to find the suitable method for evaluating candidates or ranking alternatives based on provided ordinal information and criteria, and this in many cases is to rank alternatives based on qualitative ordering information. In this paper, we discuss the importance and research aspects of ordering based decision making, and review the existing ordering based decision making theories and methods along with some future research directions

Collective decision-making with goals

Des agents devant prendre une décision collective sont souvent motivés par des buts individuels. Dans ces situations, deux aspects clés doivent être abordés : sélectionner une alternative gagnante à partir des voix des agents et s'assurer que les agents ne manipulent pas le résultat. Cette thèse étudie l'agrégation et la dimension stratégique des décisions collectives lorsque les agents utilisent un langage représenté de manière compacte. Nous étudions des langages de type logique : de la logique propositionnelle aux CP-nets généralisés, en passant par la logique temporelle linéaire (LTL). Notre principale contribution est l'introduction d'un cadre de vote sur les buts, dans lequel les agents soumettent des buts individuels exprimés comme des formules de la logique propositionnelle. Les fonctions d'agrégation classiques issues du vote, de l'agrégation de jugements et de la fusion de croyances sont adaptées et étudiées de manière axiomatique et computationnelle. Les propriétés axiomatiques connues dans la littérature sur la théorie du choix social sont généralisées à ce nouveau type d'entrée, ainsi que les problèmes de complexité visant à déterminer le résultat du vote. Une autre contribution importante est l'étude de l'agrégation des CP-nets généralisés, c'est-à-dire des CP-nets où la précondition de l'énoncé de préférence est une formule propositionnelle. Nous utilisons différents agrégateurs pour obtenir un classement collectif des résultats possibles. Grâce à cette thèse, deux axes de recherche sont ainsi reliés : l'agrégation des CP-nets classiques et la généralisation des CP-nets à des préconditions incomplètes. Nous contribuons également à l'étude du comportement stratégique dans des contextes de prise de décision collective et de théorie des jeux. Le cadre du vote basé sur les buts est de nouveau étudié sous l'hypothèse que les agents peuvent décider de mentir sur leur but s'ils obtiennent ainsi un meilleur résultat. L'accent est mis sur trois règles de vote majoritaires qui se révèlent manipulables. Par conséquent, nous étudions des restrictions à la fois sur le langage des buts et sur les stratégies des agents en vue d'obtenir des résultats de votes non manipulables. Nous présentons par ailleurs une extension stratégique d'un modèle récent de diffusion d'opinion sur des réseaux d'influence. Dans les jeux d'influence définis ici, les agents ont comme but des formules en LTL et ils peuvent choisir d'utiliser leur pouvoir d'influence pour s'assurer que leur but est atteint. Des solutions classiques telles que la stratégie gagnante sont étudiées pour les jeux d'influence, en relation avec la structure du réseau et les buts des agents. Enfin, nous introduisons une nouvelle classe de concurrent game structures (CGS) dans laquelle les agents peuvent avoir un contrôle partagé sur un ensemble de variables propositionnelles. De telles structures sont utilisées pour interpréter des formules de logique temporelle en temps alternés (ATL), grâce auxquelles on peut exprimer l'existence d'une stratégie gagnante pour un agent dans un jeu itéré (comme les jeux d'influence mentionnés ci-dessus). Le résultat principal montre qu'un CGS avec contrôle partagé peut être représenté comme un CGS avec contrôle exclusif. En conclusion, cette thèse contribue au domaine de la prise de décision collective en introduisant un nouveau cadre de vote basé sur des buts propositionnels. Elle présente une étude de l'agrégation des CP-nets généralisés et une extension d'un cadre de diffusion d'opinion avec des agents rationnels qui utilisent leur pouvoir d'influence. Une réduction du contrôle partagé à un contrôle exclusif dans les CGS pour l'interprétation des logiques du raisonnement stratégique est également proposée. Par le biais de langages logiques divers, les agents peuvent ainsi exprimer buts et préférences sur la décision à prendre, et les propriétés souhaitées pour le processus de décision peuvent en être garanties.Agents having to take a collective decision are often motivated by individual goals. In such scenarios, two key aspects need to be addressed. The first is defining how to select a winning alternative from the expressions of the agents. The second is making sure that agents will not manipulate the outcome. Agents should also be able to state their goals in a way that is expressive, yet not too burdensome. This dissertation studies the aggregation and the strategic component of multi-agent collective decisions where the agents use a compactly represented language. The languages we study are all related to logic: from propositional logic, to generalized CP-nets and linear temporal logic (LTL). Our main contribution is the introduction of the framework of goal-based voting, where agents submit individual goals expressed as formulas of propositional logic. Classical aggregation functions from voting, judgment aggregation, and belief merging are adapted to this setting and studied axiomatically and computationally. Desirable axiomatic properties known in the literature of social choice theory are generalized to this new type of propositional input, as well as the standard complexity problems aimed at determining the result. Another important contribution is the study of the aggregation of generalized CP-nets coming from multiple agents, i.e., CP-nets where the precondition of the preference statement is a propositional formula. We use different aggregators to obtain a collective ordering of the possible outcomes. Thanks to this thesis, two lines of research are thus bridged: the one on the aggregation of complete CP-nets, and the one on the generalization of CP-nets to incomplete preconditions. We also contribute to the study of strategic behavior in both collective decision-making and game-theoretic settings. The framework of goal-based voting is studied again under the assumption that agents can now decide to submit an untruthful goal if by doing so they can get a better outcome. The focus is on three majoritarian voting rules which are found to be manipulable. Therefore, we study restrictions on both the language of the goals and on the strategies allowed to the agents to discover islands of strategy-proofness. We also present a game-theoretic extension of a recent model of opinion diffusion over networks of influence. In the influence games defined here, agents hold goals expressed as formulas of LTL and they can choose whether to use their influence power to make sure that their goal is satisfied. Classical solution concepts such as weak dominance and winning strategy are studied for influence games, in relation to the structure of the network and the goals of the agents. Finally, we introduce a novel class of concurrent game structures (CGS) in which agents can have shared control over a set of propositional variables. Such structures are used for the interpretation of formulas of alternating-time temporal logic, thanks to which we can express the existence of a winning strategy for an agent in a repeated game (as, for instance, the influence games mentioned above). The main result shows by means of a clever construction that a CGS with shared control can be represented as a CGS with exclusive control. In conclusion, this thesis provides a valuable contribution to the field of collective decision-making by introducing a novel framework of voting based on individual propositional goals, it studies for the first time the aggregation of generalized CP-nets, it extends a framework of opinion diffusion by modelling rational agents who use their influence power as they see fit, and it provides a reduction of shared to exclusive control in CGS for the interpretation of logics of strategic reasoning. By using different logical languages, agents can thus express their goals and preferences over the decision to be taken, and desirable properties of the decision process can be ensured

Probabilistic Conditional Preference Networks (JIAF 2013)

International audienceIn order to represent the preferences of a group of individuals, we introduce Probabilistic CP-nets (PCP-nets). PCP-nets provide a compact language for representing probability distributions over preference orderings. We argue that they are useful for aggregating preferences or modelling noisy preferences. Then we give efficient algorithms for the main reasoning problems, namely for computing the probability that a given outcome is preferred to another one, and the probability that a given outcome is optimal. As a by-product, we obtain an unexpected linear-time algorithm for checking dominance in a standard, tree-structured CP-net.Afin de représenter les préférences d’un groupe d’individus, nous introduisons les CP-nets probabilistes (PCP-net). Les PCP-nets fournissent un langage compact pour représenter des distributions de probabilités sur des ordres de préférences. Nous pensons qu’ils sont utiles pour modéliser des agrégations de préférences ou encore des préférences bruitées. Puis, nous proposons des algorithmes efficaces pour les principaux problèmes de raisonnement ; par exemple pour calculer la probabilité qu’un objet donné est préféré `a un autre, ou encore la probabilité qu’un objet donné est optimal. En tant que résultat dérivé, on obtient un algorithme, en temps linéaire inattendu, de contrôle de la dominance pour une structure arborescente

Vote and aggregation in combinatorial domains with structured preferences

In many real-world collective decision problems, the set of alternatives is a Cartesian product of finite value domains for each of a given set of variables. The prohibitive size of such combinatorial domains makes it practically impossible to represent preference relations explicitly. Now, the AI community has been developing languages for representing preferences on such domains in a succinct way, exploiting structural properties such as conditional preferential independence. In this paper we reconsider voting and aggregation rules in the case where voters' preferences have a common preferential independence structure, and address the issue of decomposing a voting rule or an aggregation function following a linear order over variables

Of cattle, sand flies and men : a systematic review of risk factor analyses for South Asian visceral leishmaniasis and implications for elimination

Background: Studies performed over the past decade have identified fairly consistent epidemiological patterns of risk factors for visceral leishmaniasis (VL) in the Indian subcontinent. Methods and Principal Findings: To inform the current regional VL elimination effort and identify key gaps in knowledge, we performed a systematic review of the literature, with a special emphasis on data regarding the role of cattle because primary risk factor studies have yielded apparently contradictory results. Because humans form the sole infection reservoir, clustering of kala-azar cases is a prominent epidemiological feature, both at the household level and on a larger scale. Subclinical infection also tends to show clustering around kala-azar cases. Within villages, areas become saturated over a period of several years; kala-azar incidence then decreases while neighboring areas see increases. More recently, post kalaazar dermal leishmaniasis (PKDL) cases have followed kala-azar peaks. Mud walls, palpable dampness in houses, and peridomestic vegetation may increase infection risk through enhanced density and prolonged survival of the sand fly vector. Bed net use, sleeping on a cot and indoor residual spraying are generally associated with decreased risk. Poor micronutrient status increases the risk of progression to kala-azar. The presence of cattle is associated with increased risk in some studies and decreased risk in others, reflecting the complexity of the effect of bovines on sand fly abundance, aggregation, feeding behavior and leishmanial infection rates. Poverty is an overarching theme, interacting with individual risk factors on multiple levels. Conclusions: Carefully designed demonstration projects, taking into account the complex web of interconnected risk factors, are needed to provide direct proof of principle for elimination and to identify the most effective maintenance activities to prevent a rapid resurgence when interventions are scaled back. More effective, short-course treatment regimens for PKDL are urgently needed to enable the elimination initiative to succeed

04271 Abstracts Collection -- Preferences: Specification, Inference, Applications

From 27.06.04 to 02.07.04, the Dagstuhl Seminar 04271 ``Preferences: Specification, Inference, Applications\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. During the seminar, several participants presented their current research, and ongoing work and open problems were discussed. Abstracts of the presentations given during the seminar as well as abstracts of seminar results and ideas are put together in this paper. The first section describes the seminar topics and goals in general. Links to extended abstracts or full papers are provided, if available