A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Preference programming: Advanced problem solving for configuration
2003
Artificial intelligence for engineering design, analysis and manufacturing
Preserved Fulltext
Preference programming provides a new paradigm for expressing (default) decisions, preferences between decisions, and search strategies in a declarative and unified way and for embedding them in a constraint ...
Business experts can thus directly specify preferences and search directives in form of rules without needing to program search strategies as required by constraint programming based configuration tools ...
For helpful remarks, I also want to thank Xavier Ceugniet, Daniel Mailharro, and Jean-François Puget. ...
doi:10.1017/s089006040317103x
fatcat:2drga6t4inhudj63lg324dt2py
Constructive Preference Elicitation
2018
Frontiers in Robotics and AI
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
In this article, we describe recent approaches especially designed for constructive problems, outlining the underlying ideas and their differences as well as their limitations. ...
They do so by interactively learning the DM's preferences through appropriately chosen queries and suggesting high-quality outcomes based on the preference estimates. ...
This allows to encode arbitrary inference problems using arbitrary modeling frameworks, e.g., constraint programming in our case, to solve various constructive applications, as shown in the next sections ...
doi:10.3389/frobt.2017.00071
fatcat:kjp2a2e6sjchzausnyqeur6tym
Fuzzy Preference Programming Framework for Functional Assessment of Subway Networks
2020
Algorithms
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The model uses the Fuzzy Analytical Network Process with application to Fuzzy Preference Programming to calculate the weights for seven failure impact attributers and seven criticality attributes. ...
With multiple assets competing for the limited fund, new methodologies are required to prioritize assets for rehabilitation. ...
It can be concluded that FPP transforms the prioritization problem into a linear program that can easily be solved by standard simplex technique. ...
doi:10.3390/a13090220
fatcat:m7za7ysewnezxlsjvrnwtaon34
Trends in preference, programming and design of concert halls for symphonic music
2008
Journal of the Acoustical Society of America
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Using this impedance condition a finite element problem can be solved by standard methods. ...
Listeners' ability to parse concurrent sounds is a prerequisite in solving the cocktail party problem. ...
In this paper, a low-damping vibration absorber is studied for solving noise radiation problems from a resonant, light-gauge structure driven by a force whose frequency and amplitude are constant and whose ...
doi:10.1121/1.2932471
fatcat:hhka5ml2fvcszklkzau2lw3gka
Learning Modulo Theories for preference elicitation in hybrid domains
[article]
2015
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
While no competitors exist in the hybrid setting, CLEO outperforms a state-of-the-art Bayesian preference elicitation algorithm when applied to a purely discrete task. ...
This paper introduces CLEO, a novel preference elicitation algorithm capable of recommending complex objects in hybrid domains, characterized by both discrete and continuous attributes and constraints ...
Figure 2 : 2 Performance of CLEO while solving the housing problem. ...
arXiv:1508.04261v3
fatcat:zagrnbte3zfmljfbzq4ub3t4ru
Decomposition Strategies for Constructive Preference Elicitation
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We propose a decomposition technique for large preference-based decision problems relying exclusively on inference and feedback over partial configurations. ...
In this setting, the suggested configuration is synthesized on-the-fly by solving a constrained optimization problem, while the preferences are learned itera tively by interacting with the user. ...
Copyright c 2018, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. customer's preferences. ...
arXiv:1711.08247v2
fatcat:bcelxdnjcbc3jcmejjbbwffipq
Preferences and Nonmonotonic Reasoning
2008
The AI Magazine
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
Conflicts among program rules (more generally, defaults) give rise to alternative preferred belief sets. ...
Selecting extended logic programming with the answer-set semantics as a "generic" nonmonotonic logic, we show how that logic defines preferred belief sets and how preferred belief sets allow us to represent ...
Acknowledgments We thank the reviewers for helpful comments. Ilkka Niemelä acknowledges the support of Academy of Finland grant 122399. ...
doi:10.1609/aimag.v29i4.2179
fatcat:2qrcipfj3fd3lirr24go6smm5m
Expressing advanced user preferences in component installation
[article]
2009
arXiv
pre-print
Preserved Fulltext
The Internet Archive has a preservation copy of this work in our general collections.
The file type is application/pdf.
Other Versions
2009
Proceedings of the 1st international workshop on Open component ecosystems - IWOCE '09
unpublished
doi:10.1145/1595800.1595806 fatcat:juqepb3e5vhwzd2qv7rvcfktj4
doi:10.1145/1595800.1595806 fatcat:juqepb3e5vhwzd2qv7rvcfktj4
We present an architecture that allows to express advanced user preferences about package selection in FOSS distributions. ...
The architecture is composed by a distribution-independent format for describing available and installed packages called CUDF (Common Upgradeability Description Format), and a foundational language called ...
While suitable and complete techniques to provide dependency solving completeness are now well-known [9] and "just" lack widespread adoption, handling of complex user preferences is a novel problem for ...
arXiv:0909.5091v1
fatcat:54owtua4i5d5th46culwabubvm
Sequential decision making with partially ordered preferences
2011
Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Sequential decision making under uncertainty Partially ordered preferences Sets of probability measures Criteria of choice Consequentialist and resolute norms Linear and multilinear programming This paper ...
presents new insights and novel algorithms for strategy selection in sequential decision making with partially ordered preferences; that is, where some strategies may be incomparable with respect to expected ...
To find a * we must solve n optimization programs; to determine the set of admissible actions we must solve n − 1 additional optimization programs. ...
doi:10.1016/j.artint.2010.11.017
fatcat:jsjoszponrfxdiw4daummduwpq
Predicting Academic Course Preference using Hadoop
2019
International journal of recent technology and engineering
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
To avoid this problem we are using Mapreduce for decision making of students in order to choose their preferred course for industrial training purpose for their effective learning techniques to increase ...
And this leads to huge amounts of data which makes a big challenge for the students to store the preferred course. ...
The advanced algorithms have been coded by the knowledge scientists for frameworks so that it becomes easy to use for the programmers. ...
doi:10.35940/ijrte.d7123.118419
fatcat:h7m7eakqz5eybmpsyjsabwultu
Evolving Random Forest for Preference Learning
[chapter]
2015
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The combination of these two efficient methods for evolution and modelling yields a powerful technique for learning pairwise preferences. ...
This paper introduces a novel approach for pairwise preference learning through a combination of an evolutionary method and random forest. ...
Martinez for valuable discussions. ...
doi:10.1007/978-3-319-16549-3_26
fatcat:bkklabw3gfdbdmd7ljdakxqnfm
Preferences in artificial intelligence
2015
Annals of Mathematics and Artificial Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
of constraint programming in order to solve preference aggregation and recommendation problems. ...
can be solved (see for instance [257] ). ...
doi:10.1007/s10472-015-9475-5
fatcat:3wspv5ycirgapjv6u2bxpcd6p4
Arc Consistency for Constrained Lexicographic Preference Trees
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The empirical results conducted on the new structure show the feasibility of applying AC to further simplify the problem and solve it. ...
For more information, see https://creativecommons.org/licenses/by/4.0/ VOLUME 8, 2020 INDEX TERMS ...
For instance, in product configuration, the user has preferences on different components of the product but some components are not compatible with the each other. ...
doi:10.1109/access.2020.2983283
fatcat:5ymtye4vmvdkzpu3tsxa4owifu
Weight Constraints with Preferences in ASP
[chapter]
2011
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Preference-based reasoning is a form of commonsense reasoning that makes many problems easier to express and sometimes more likely to have a solution. ...
In this paper, we present an approach to introducing preferences in the weight constraint construct, which is a very useful programming construct widely adopted in Answer Set Programming (ASP). ...
For instance, the motivating example discussed in [8] concerns scheduling problems to be solved according to both preferences and priorities. ...
doi:10.1007/978-3-642-20895-9_24
fatcat:syqs4pifvfgfbblnfdkxidz3ny
Program
2019
2019 IEEE Global Conference on Internet of Things (GCIoT)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The existing proposals to solve the Massive Access Problem model the traffic generation pattern of each IoT device via random arrivals. ...
In contrast, our JFS system forecasts the traffic generation pattern of each IoT device and schedules the transmissions of these devices in advance. ...
Thus it can be used to derive security configurations for each individual embedded device, it's services and the network as a whole. ...
doi:10.1109/gciot47977.2019.9058389
fatcat:z62yf6bds5flhdatcvsuzzkj5q
« Previous
Showing results 1 — 15 out of 119,182 results