13,616 research outputs found
A semantical approach to equilibria and rationality
Game theoretic equilibria are mathematical expressions of rationality.
Rational agents are used to model not only humans and their software
representatives, but also organisms, populations, species and genes,
interacting with each other and with the environment. Rational behaviors are
achieved not only through conscious reasoning, but also through spontaneous
stabilization at equilibrium points.
Formal theories of rationality are usually guided by informal intuitions,
which are acquired by observing some concrete economic, biological, or network
processes. Treating such processes as instances of computation, we reconstruct
and refine some basic notions of equilibrium and rationality from the some
basic structures of computation.
It is, of course, well known that equilibria arise as fixed points; the point
is that semantics of computation of fixed points seems to be providing novel
methods, algebraic and coalgebraic, for reasoning about them.Comment: 18 pages; Proceedings of CALCO 200
Solving Hard Control Problems in Voting Systems via Integer Programming
Voting problems are central in the area of social choice. In this article, we
investigate various voting systems and types of control of elections. We
present integer linear programming (ILP) formulations for a wide range of
NP-hard control problems. Our ILP formulations are flexible in the sense that
they can work with an arbitrary number of candidates and voters. Using the
off-the-shelf solver Cplex, we show that our approaches can manipulate
elections with a large number of voters and candidates efficiently
Dealing with inconsistent judgments in multiple criteria sorting models.
Sorting models consist in assigning alternatives evaluated on several criteria to ordered categories. To implement such models it is necessary to set the values of the preference parameters used in the model. Rather than fixing the values of these parameters directly, a usual approach is to infer these values from assignment examples provided by the decision maker (DM), i.e., alternatives for which (s)he specifies a required category. However, assignment examples provided by DMs can be inconsistent, i.e., may not match the sorting model. In such situations, it is necessary to support the DMs in the resolution of this inconsistency. In this paper, we extend algorithms from Mousseau et al.(2003) that calculate different ways to remove assignment examples so that the information can be represented in the sorting model. The extension concerns the possibility to relax (rather than to delete) assignment examples. These algorithms incorporate information about the confidence attached to each assignment example, hence providing inconsistency resolutions that the DMs are most likely to accept.Multicriteria decision aiding; Inconsistency analysis; Sorting problem;
Reasons and Means to Model Preferences as Incomplete
Literature involving preferences of artificial agents or human beings often
assume their preferences can be represented using a complete transitive binary
relation. Much has been written however on different models of preferences. We
review some of the reasons that have been put forward to justify more complex
modeling, and review some of the techniques that have been proposed to obtain
models of such preferences
On Estimating Multi-Attribute Choice Preferences using Private Signals and Matrix Factorization
Revealed preference theory studies the possibility of modeling an agent's
revealed preferences and the construction of a consistent utility function.
However, modeling agent's choices over preference orderings is not always
practical and demands strong assumptions on human rationality and
data-acquisition abilities. Therefore, we propose a simple generative choice
model where agents are assumed to generate the choice probabilities based on
latent factor matrices that capture their choice evaluation across multiple
attributes. Since the multi-attribute evaluation is typically hidden within the
agent's psyche, we consider a signaling mechanism where agents are provided
with choice information through private signals, so that the agent's choices
provide more insight about his/her latent evaluation across multiple
attributes. We estimate the choice model via a novel multi-stage matrix
factorization algorithm that minimizes the average deviation of the factor
estimates from choice data. Simulation results are presented to validate the
estimation performance of our proposed algorithm.Comment: 6 pages, 2 figures, to be presented at CISS conferenc
Valuation of cow attributes by conjoint analysis: A case study of Western Kenya
Better dairy production could reduce poverty and improve nutrition in western Kenya, but the requisite technologies have not been widely adopted. This study collected dairy cow attributes from 630 households to evaluate what factors influence smallholder farmers to adopt technologies. Conjoint analysis was used to compute the marginal rate of substitution between attributes, marginal willingness to pay, and marginal willingness to accept. Two ethnic groups had the highest willingness to pay for cattle with a high milk yield and low feed requirement. The highest marginal rate of substitution for cattle with a high disease resistance and a low feed requirement was from households with off-farm income, from areas with a good agro-climate, and from areas where cattle had cultural functions. The results suggest that farmers are more likely to choose cross-bred than high grade cows, and that extension services have little effect on their adoption of dairy technology. Kenya’s breed policy and infrastructure may need to be revised to reflect farmers’ needs.Conjoint analysis, valuation of cow attributes, dairy production, Kenya, Livestock Production/Industries,
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