This paper studies the use of product-based possibilistic networks for representing preferences in multidimensional decision problems. This approach uses symbolic possibility weights and defines a partial preference o...
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This paper studies the use of product-based possibilistic networks for representing preferences in multidimensional decision problems. This approach uses symbolic possibility weights and defines a partial preference order among solutions to a set of conditional preference statements on the domains of discrete decision variables. In the case of Boolean decision variables, this partial ordering is shown to be consistent with the preference ordering induced by the ceteris paribus assumption adopted in CP-nets. Namely, by completing the possibilistic net ordering with suitable constraints between products of symbolic weights, all CP-net preferences can be recovered. Computing procedures for comparing solutions are provided. The flexibility and representational power of the approach is stressed. (C) 2017 Elsevier Inc. All rights reserved.
We study strategic behaviour in goal-based voting, where agents take a collective decision over multiple binary issues based on their individual goals (expressed as propositional formulas). We focus on three generaliz...
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ISBN:
(纸本)9781450363099
We study strategic behaviour in goal-based voting, where agents take a collective decision over multiple binary issues based on their individual goals (expressed as propositional formulas). We focus on three generalizations of the issue-wise majority rule, and study their resistance to manipulability in the general case, as well as for restricted languages for goals. We also study how computationally hard it is for an agent to know if they can profitably manipulate.
This paper presents use of a tool built to monitor human-website interaction without the need for eye tracking. Behavior indicators calculated from data collected by the tool can be used for many purposes such as web ...
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This paper presents use of a tool built to monitor human-website interaction without the need for eye tracking. Behavior indicators calculated from data collected by the tool can be used for many purposes such as web ergonomics enhancement, content adaptation, and, in particular, recommender systems. A random-forests-based modeling approach is shown as a generalization for earlier decision-tree classification approach. Results of a usability survey conducted within the study are presented.
In this study, we investigate travel mode choice behavior between taxi and subway with an emphasis on the influence of traveling convenience. In the first stage, we examine the Origin-Destination(OD) points of Beijing...
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In this study, we investigate travel mode choice behavior between taxi and subway with an emphasis on the influence of traveling convenience. In the first stage, we examine the Origin-Destination(OD) points of Beijing taxi trips and compare these locations with the respective nearest subway station. Statistics reveal several interesting conclusions. First, for approximately 24.89% of all trips, no convenient subway connections exist between the OD pairs. As such, a taxi becomes the only viable choice. Second, for 80.23% of the remaining 75.11%of trips(equivalent to 60.26% of all trips), access distance from either the origin or the destination to the nearest subway station is greater than 500 meters. This phenomenon indicates that walking distance plays an important role in travel mode choice. In the second stage, we examine groups of taxi trips with similar travel distances and travel times to reveal common features. We establish a preference rule in terms of travel distance and travel *** determines whether an individual driver will take a taxi or the subway, using a pairwise comparison-based preference regression model. Tests indicate that more than 95% of taxi trips can be correctly predicted by this preference rule. This conclusion reveals that traveling convenience dominates the travel model choice between taxi and subway. All these findings shed light on the factors that influence travel mode choice behavior.
Accommodation accounts for one of the biggest expenses while traveling, and deciding where to stay is often confusing and time-consuming. Fortunately, travelers have more options than ever before because of the substa...
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Accommodation accounts for one of the biggest expenses while traveling, and deciding where to stay is often confusing and time-consuming. Fortunately, travelers have more options than ever before because of the substantial growth of the peer-to-peer (P2P) short-term rentals in the sharing economy. Designing a user-friendly system that considers travelers' preferences in choosing the right accommodation can enhance customer satisfaction and increase profitability. We propose a dynamic decision support system based on the theory of multicriteria decision making to assist travelers in personalizing their preferences and finding quality accommodations in the dominant P2P market that aligns with those preferences. We use the fuzzy best-worst method to measure the intensity of the user's preferences and the fuzzy technique for order of preference by similarity to the ideal solution (TOPSIS) to score and evaluate alternative P2P rental properties. We present a case study in the P2P rental accommodations industry to demonstrate the applicability of the method proposed in this study.
For optimisation problems with multiple objectives and large search spaces, it may not be feasible to find all optimal solutions. Even if possible, a decision maker (DM) is only interested in a small number of these s...
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ISBN:
(纸本)9781450356183
For optimisation problems with multiple objectives and large search spaces, it may not be feasible to find all optimal solutions. Even if possible, a decision maker (DM) is only interested in a small number of these solutions. Incorporating a DM's solution preferences into the process reduces the problem's search space by focusing only on regions of interest. Allowing a DM to interact and alter their preferences during a single optimisation run facilitates learning and mistake correction, and improves the search for desired solutions. In this paper, we apply an interactive framework to four leading multi-objective evolutionary algorithms (MOEAs), which use reference points to model preferences. Furthermore, we propose a new performance metric for algorithm responsiveness to preference changes, and evaluate these algorithms using this metric. Interactive algorithms must respond to changes in DM preferences and we show how our new metric is able to differentiate between the four algorithms when run on the ZDT suite of test problems. Finally, we identify characteristics of these methods that determine their level of response to change.
Can non-classical logic contribute to the analysis of complexity in computer science? In this paper, we give a step towards the solution of this open problem, taking a logical model-theoretic approach to the analysis ...
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ISBN:
(纸本)9783030002022;9783030002015
Can non-classical logic contribute to the analysis of complexity in computer science? In this paper, we give a step towards the solution of this open problem, taking a logical model-theoretic approach to the analysis of complexity in fuzzy constraint satisfaction. We study fuzzy positive-primitive sentences, and we present an algebraic characterization of classes axiomatized by this kind of sentences in terms of homomorphisms and finite direct products. The ultimate goal is to study the expressiveness and reasoning mechanisms of non-classical languages, with respect to constraint satisfaction problems and, in general, in modelling decision scenarios.
作者:
De Mol, RobinDe Tre, GuyUniv Ghent
Fac Engn & Architecture Dept Telecommun & Informat Proc Databases Documents & Content Management Res Grp Sint Pietersnieuwstr 41 B-9000 Ghent Belgium
Some industrial purposes require specific marine resources. Companies rely on information from resource models to decide where to go and what the cost will be to perform the required extractions. Such models, however,...
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ISBN:
(纸本)9783319914732;9783319914725
Some industrial purposes require specific marine resources. Companies rely on information from resource models to decide where to go and what the cost will be to perform the required extractions. Such models, however, are typical examples of imprecise data sets wherein most data is estimated rather than measured. This is especially true for marine resource models, for which acquiring real data samples is a long and costly endeavor. Consequently, such models are largely computed by interpolating data from a small set of measurements. In this paper, we discuss how we have applied fuzzy set theory on a real data set to deal with these issues. It is further explained how the resulting fuzzy model can be queried so it may be used in a decision making context. To evaluate queries, we use a novel preference modeling and evaluation technique specifically suited for dealing with uncertain data, based on suitability distributions. The technique is illustrated by evaluating an example query and discussing the results.
This paper presents use of a tool built to monitor human-website interaction without the need for eye tracking. Behavior indicators calculated from data collected by the tool can be used for many purposes such as web ...
详细信息
This paper presents use of a tool built to monitor human-website interaction without the need for eye tracking. Behavior indicators calculated from data collected by the tool can be used for many purposes such as web ergonomics enhancement, content adaptation, and, in particular, recommender systems. A random-forests-based modeling approach is shown as a generalization for earlier decision-tree classification approach. Results of a usability survey conducted within the study are presented.
We study strategic behaviour in goal-based voting, where agents take a collective decision over multiple binary issues based on their individual goals (expressed as propositional formulas). We focus on three generaliz...
详细信息
ISBN:
(纸本)9781450363099
We study strategic behaviour in goal-based voting, where agents take a collective decision over multiple binary issues based on their individual goals (expressed as propositional formulas). We focus on three generalizations of the issue-wise majority rule, and study their resistance to manipulability in the general case, as well as for restricted languages for goals. We also study how computationally hard it is for an agent to know if they can profitably manipulate.
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