Going from Theory to Practice: The Mixed Success of Approval Voting

Approval voting (AV) is a voting system in which voters can vote for, or approve of, as many candidates as they like in multicandidate elections. In 1987 and 1988, four scientific and engineering societies, collectively comprising several hundred thousand members, used AV for the first time. Since then, about half a dozen other societies have adopted AV. Usually its adoption was seriously debated, but other times pragmatic or political considerations proved decisive in its selection. While AV has an ancient pedigree, its recent history is the focus of this paper. Ballot data from some of the societies that adopted AV are used to compare theoretical results with experience, including the nature of voting under AV and the kinds of candidates that are elected. Although the use of AV is generally considered to have been successful in the societies-living up to the rhetoric of its proponents-AV has been a controversial reform. AV is not currently used in any public elections, despite efforts to institute it, so its success should be judged as mixed. The chief reason for its nonadoption in public elections, and by some societies, seems to be a lack of key "insider" support.APPROVAL VOTING; ELECTIONS; PROFESSIONAL SOCIETIES; CONDORCET CANDIDATE.

Stable marriage with general preferences

We propose a generalization of the classical stable marriage problem. In our model, the preferences on one side of the partition are given in terms of arbitrary binary relations, which need not be transitive nor acyclic. This generalization is practically well-motivated, and as we show, encompasses the well studied hard variant of stable marriage where preferences are allowed to have ties and to be incomplete. As a result, we prove that deciding the existence of a stable matching in our model is NP-complete. Complementing this negative result we present a polynomial-time algorithm for the above decision problem in a significant class of instances where the preferences are asymmetric. We also present a linear programming formulation whose feasibility fully characterizes the existence of stable matchings in this special case. Finally, we use our model to study a long standing open problem regarding the existence of cyclic 3D stable matchings. In particular, we prove that the problem of deciding whether a fixed 2D perfect matching can be extended to a 3D stable matching is NP-complete, showing this way that a natural attempt to resolve the existence (or not) of 3D stable matchings is bound to fail.Comment: This is an extended version of a paper to appear at the The 7th International Symposium on Algorithmic Game Theory (SAGT 2014

Processing second-order stochastic dominance models using cutting-plane representations

This is the post-print version of the Article. The official published version can be accessed from the links below. Copyright @ 2011 Springer-VerlagSecond-order stochastic dominance (SSD) is widely recognised as an important decision criterion in portfolio selection. Unfortunately, stochastic dominance models are known to be very demanding from a computational point of view. In this paper we consider two classes of models which use SSD as a choice criterion. The first, proposed by Dentcheva and Ruszczyński (J Bank Finance 30:433–451, 2006), uses a SSD constraint, which can be expressed as integrated chance constraints (ICCs). The second, proposed by Roman et al. (Math Program, Ser B 108:541–569, 2006) uses SSD through a multi-objective formulation with CVaR objectives. Cutting plane representations and algorithms were proposed by Klein Haneveld and Van der Vlerk (Comput Manage Sci 3:245–269, 2006) for ICCs, and by Künzi-Bay and Mayer (Comput Manage Sci 3:3–27, 2006) for CVaR minimization. These concepts are taken into consideration to propose representations and solution methods for the above class of SSD based models. We describe a cutting plane based solution algorithm and outline implementation details. A computational study is presented, which demonstrates the effectiveness and the scale-up properties of the solution algorithm, as applied to the SSD model of Roman et al. (Math Program, Ser B 108:541–569, 2006).This study was funded by OTKA, Hungarian National Fund for Scientific Research, project 47340; by Mobile Innovation Centre, Budapest University of Technology, project 2.2; Optirisk Systems, Uxbridge, UK and by BRIEF (Brunel University Research Innovation and Enterprise Fund)

Combining Interval and Probabilistic Uncertainty: What Is Computable?

In many practical problems, we need to process measurement results. For example, we need such data processing to predict future values of physical quantities. In these computations, it is important to take into account that measurement results are never absolutely exact, that there is always measurement uncertainty, because of which the measurement re-sults are, in general, somewhat different from the actual (unknown) values of the corresponding quantities. In some cases, all we know about mea-surement uncertainty is an upper bound; in this case, we have an interval uncertainty, meaning that all we know about the actual value is that is belongs to a certain interval. In other cases, we have some information – usually partial – about the corresponding probability distribution. New data processing challenges appear all the time; in many of these cases, it is important to come up with appropriate algorithms for taking uncertainty into account

Rationality in context: An analogical perspective

At times, human behavior seems erratic and irrational. Therefore, when modeling human decision-making, it seems reasonable to take the remarkable abilities of humans into account with respect to rational behavior, but also their apparent deviations from the normative standards of rationality shining up in certain rationality tasks. Based on well-known challenges for human rationality, together with results from psychological studies on decision-making and from previous work in the field of computational modeling of analogy-making, I argue that the analysis and modeling of rational belief and behavior should also consider context-related cognitive mechanisms like analogy-making and coherence maximization of the background theory. Subsequently, I conceptually outline a high-level algorithmic approach for a Heuristic Driven Theory Projection-based system for simulating context-dependent human-style rational behavior. Finally, I show and elaborate on the close connections, but also on the significant differences, of this approach to notions of "ecological rationality"

A Model of User Preferences for Semantic Services Discovery and Ranking

Current proposals on Semantic Web Services discovery and ranking are based on user preferences descriptions that often come with insufficient expressiveness, consequently making more difficult or even preventing the description of complex user desires. There is a lack of a general and comprehensive preference model, so discovery and ranking proposals have to provide ad hoc preference descriptions whose expressiveness depends on the facilities provided by the corresponding technique, resulting in user preferences that are tightly coupled with the underlying formalism being used by each concrete solution. In order to overcome these problems, in this paper an abstract and sufficiently expressive model for defining preferences is presented, so that they may be described in an intuitively and user-friendly manner. The proposed model is based on a well-known query preference model from database systems, which provides highly expressive constructors to describe and compose user preferences semantically. Furthermore, the presented proposal is independent from the concrete discovery and ranking engines selected, and may be used to extend current Semantic Web Service frameworks, such as wsmo, sawsdl, or owl-s. In this paper, the presented model is also validated against a complex discovery and ranking scenario, and a concrete implementation of the model in wsmo is outlined.Comisión Interministerial de Ciencia y Tecnología TIN2006-00472Comisión Interministerial de Ciencia y Tecnología TIN2009-07366Junta de Andalucía TIC-253

Galactic vs. Extragalactic Origin of the Peculiar Transient SCP 06F6

We study four scenarios for the SCP 06F6 transient event that was announced recently. Some of these were previously briefly discussed as plausible models for SCP 06F6, in particular with the claimed detection of a z=0.143 cosmological redshift of a Swan spectrum of a carbon rich envelope. We adopt this value of z for extragalactic scenarios. We cannot rule out any of these models, but can rank them from most to least preferred. Our favorite model is a tidal disruption of a CO white dwarf (WD) by an intermediate-mass black hole (IMBH). To account for the properties of the SCP 06F6 event, we have to assume the presence of a strong disk wind that was not included in previous numerical simulations. If the IMBH is the central BH of a galaxy, this explains the non detection of a bright galaxy in the direction of SCP 06F6. Our second favorite scenario is a type Ia-like SN that exploded inside the dense wind of a carbon star. The carbon star is the donor star of the exploded WD. Our third favorite model is a Galactic source of an asteroid that collided with a WD. Such a scenario was discussed in the past as the source of dusty disks around WDs, but no predictions exist regarding the appearance of such an event. Our least favorite model is of a core collapse SN. The only way we can account for the properties of SCP 06F6 with a core collapse SN is if we assume the occurrence of a rare type of binary interaction.Comment: Accepted by New Astronom

A Test of Rank-Dependent Utility in the Context of Ambiguity

Experimental investigations of non-expected utility have primarily concentrated on decision under risk (probability triangles). The literature suggests, however, that ambiguity is one of the main causes for deviations from expected utility (EU). This article investigates the descriptive performance of rank-dependent utility (RDU) in the context of choice under ambiguity. We use the axiomatic difference between RDU and EU to critically test RDU against EU. Surprisingly, the RDU model does not provide any descriptive improvement over EU. Our data suggest other framing factors that do provide descriptive improvements over EU

An axiomatization of cumulative prospect theory

This paper presents a method for axiomatizing a variety of models for decision making under uncertainty, including Expected Utility and Cumulative Prospect Theory. This method identifies, for each model, the situations that permit consistent inferences about the ordering of value differences. Examples of rankdependent and sign-dependent preference patterns are used to motivate the models and the tradeoff consistency axioms that characterize them. The major properties of the value function in Cumulative Prospect Theory—diminishing sensitivity and loss aversion—are contrasted with the principle of diminishing marginal utility that is commonly assumed in Expected Utility