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Articles 1  30 of 64
FullText Articles in Computer Engineering
How To Bargain: An Interval Approach, Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta
How To Bargain: An Interval Approach, Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta
Departmental Technical Reports (CS)
In many reallife situations, we need to bargain. What is the best bargaining strategy? If you are already in a negotiating process, your previous offer was a, the seller's last offer was A > a, what next offer a' should you make? A usual commonsense recommendation is to "split the difference", i.e., to offer a' = (a + A) / 2, or, more generally, to offer a linear combination a' = k * A + (1  k) * a (for some parameter k from the interval (0,1)).
The bargaining problem falls under the scope of the theory of cooperative games. In cooperative games, there are ...
From Program Synthesis To Optimal Program Synthesis, Joaquin Reyna
From Program Synthesis To Optimal Program Synthesis, Joaquin Reyna
Departmental Technical Reports (CS)
In many practical situations, we know the values of some quantities x_{1}, ..., x_{n}, we know the relations between these quantities, the desired quantity y, and maybe some auxiliary quantities, and we want to estimate y. There exist automatic tools for such estimations  called program synthesis tools.
A program synthesis tool usually generates a program for computing y. In many cases, however, several such programs are possible, and it is desirable to generate the optimal (e.g., the fastest) program. In this paper, we describe algorithms aimed at such optimal program synthesis.
The problem can be interpreted in logical ...
Fundamental Physical Equations Can Be Derived By Applying Fuzzy Methodology To Informal Physical Ideas, Eric Gutierrez, Vladik Kreinovich
Fundamental Physical Equations Can Be Derived By Applying Fuzzy Methodology To Informal Physical Ideas, Eric Gutierrez, Vladik Kreinovich
Departmental Technical Reports (CS)
How To Tell When A Product Of Two Partially Ordered Spaces Has A Certain Property: General Results With Application To Fuzzy Logic, Francisco Zapata, Olga Kosheleva, Karen Villaverde
How To Tell When A Product Of Two Partially Ordered Spaces Has A Certain Property: General Results With Application To Fuzzy Logic, Francisco Zapata, Olga Kosheleva, Karen Villaverde
Departmental Technical Reports (CS)
In this paper, we describe how checking whether a given property F is true for a product A1 X A2 of partially ordered spaces can be reduced to checking several related properties of the original spaces Ai.
This result is useful in fuzzy logic, where, to compare our degree of confidence in several statements, we often need to combine relative confidence comparison results provided by different experts. For example, Cartesian product corresponds to the cautious approach, when our confidence in S' is higher than confidence in S if and only if all the experts are more confident in S' than ...
Reducing OverConservative Expert Failure Rate Estimates In The Presence Of Limited Data: A New Probabilistic/Fuzzy Approach, Carlos M. Ferregut, F. Joshua Campos, Vladik Kreinovich
Reducing OverConservative Expert Failure Rate Estimates In The Presence Of Limited Data: A New Probabilistic/Fuzzy Approach, Carlos M. Ferregut, F. Joshua Campos, Vladik Kreinovich
Departmental Technical Reports (CS)
Towards Optimal Sensor Placement In MultiZone Measurements, Octavio Lerma, Craig Tweedie, Vladik Kreinovich
Towards Optimal Sensor Placement In MultiZone Measurements, Octavio Lerma, Craig Tweedie, Vladik Kreinovich
Departmental Technical Reports (CS)
Mamdani Approach To Fuzzy Control, Logical Approach, What Else?, Samuel Bravo, Jaime Nava
Mamdani Approach To Fuzzy Control, Logical Approach, What Else?, Samuel Bravo, Jaime Nava
Departmental Technical Reports (CS)
Towards Chemical Applications Of DempsterShaferType Approach: Case Of Variant Ligands, Jaime Nava
Towards Chemical Applications Of DempsterShaferType Approach: Case Of Variant Ligands, Jaime Nava
Departmental Technical Reports (CS)
In many practical situations, molecules can be obtained from a "template" molecule like benzene by replacing some of its hydrogen atoms with ligands (other atoms or atom groups). There can be many possible replacements of this type. To avoid timeconsuming testing of all possible replacements, it is desirable to test some of the replacements and then extrapolate to others  so that only the promising molecules, for which the extrapolated values are desirable, will have to be synthesized and tested.
For this extrapolation, D. J. Klein and coauthors proposed to use a DempsterShafertype poset extrapolation technique developed by G.C. Rota ...
Universal Approximation With UninormBased Fuzzy Neural Networks, Andre Lemos, Vladik Kreinovich, Walmir Caminhas, Fernando Gomide
Universal Approximation With UninormBased Fuzzy Neural Networks, Andre Lemos, Vladik Kreinovich, Walmir Caminhas, Fernando Gomide
Departmental Technical Reports (CS)
Why Curvature In LCurve: Combining Soft Constraints, Uram Anibal Sosa Aguirre, Martine Ceberio, Vladik Kreinovich
Why Curvature In LCurve: Combining Soft Constraints, Uram Anibal Sosa Aguirre, Martine Ceberio, Vladik Kreinovich
Departmental Technical Reports (CS)
Adding Constraints  A (Seemingly Counterintuitive But) Useful Heuristic In Solving Difficult Problems, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich
Adding Constraints  A (Seemingly Counterintuitive But) Useful Heuristic In Solving Difficult Problems, Olga Kosheleva, Martine Ceberio, Vladik Kreinovich
Departmental Technical Reports (CS)
Intuitively, the more constraints we impose on a problem, the more difficult it is to solve it. However, in practice, difficulttosolve problems sometimes get solved when we impose additional constraints and thus, make the problems seemingly more complex. In this methodological paper, we explain this seemingly counterintuitive phenomenon, and we show that, dues to this explanation, additional constraints can serve as a useful heuristic in solving difficult problems.
Fusing Continuous And Discrete Data, On The Example Of Merging Seismic And Gravity Models In Geophysics, Omar Ochoa, Aaron Velasco, Vladik Kreinovich
Fusing Continuous And Discrete Data, On The Example Of Merging Seismic And Gravity Models In Geophysics, Omar Ochoa, Aaron Velasco, Vladik Kreinovich
Departmental Technical Reports (CS)
In many application areas, we need to fuse continuous and discrete models of the same phenomena. For example, in geophysics, we have two main models for describing how the sound velocity changes with location and depth: a discrete gravitybased model, in which we have several layers with abrupt transition between layers, and a seismic model, in which the velocity continuously changes with the change in location and depth  and a transition is represented by a steeper change. Due to inevitable uncertainty, in two fused models, the same actual transition is placed at slightly different depths.
If we simply fuse these ...
Towards Optimal Placement Of BioWeapon Detectors, Chris Kiekintveld, Octavio Lerma
Towards Optimal Placement Of BioWeapon Detectors, Chris Kiekintveld, Octavio Lerma
Departmental Technical Reports (CS)
Testing Shock Absorbers: Towards A Faster Parallelizable Algorithm, Christian Servin
Testing Shock Absorbers: Towards A Faster Parallelizable Algorithm, Christian Servin
Departmental Technical Reports (CS)
From Single To Double Use Expressions, With Applications To Parametric Interval Linear Systems: On Computational Complexity Of Fuzzy And Interval Computations, Joseph A Lorkowski
From Single To Double Use Expressions, With Applications To Parametric Interval Linear Systems: On Computational Complexity Of Fuzzy And Interval Computations, Joseph A Lorkowski
Departmental Technical Reports (CS)
Least Sensitive (Most Robust) Fuzzy "Exclusive Or" Operations, Jesus E. Hernandez, Jaime Nava
Least Sensitive (Most Robust) Fuzzy "Exclusive Or" Operations, Jesus E. Hernandez, Jaime Nava
Departmental Technical Reports (CS)
Estimating Mean Under Interval Uncertainty And Variance Constraint, Ali JalalKamali, Luc Longpre, Misha Kosheleva
Estimating Mean Under Interval Uncertainty And Variance Constraint, Ali JalalKamali, Luc Longpre, Misha Kosheleva
Departmental Technical Reports (CS)
In many practical situations, we have a sample of objects of a given type. When we measure the values of a certain quantity for these objects, we get a sequence of values x1, ..., xn. When the sample is large enough, then the arithmetic mean E of the values xi is a good approximation for the average value of this quantity for all the objects from this class.
The values xi come from measurements, and measurements are never absolutely accurate. Often, the only information that we have about the measurement error is the upper bound Di on this error. In this ...
Computing The Range Of VarianceToMean Ratio Under Interval And Fuzzy Uncertainty, SioLong Lo, Gang Xiang
Computing The Range Of VarianceToMean Ratio Under Interval And Fuzzy Uncertainty, SioLong Lo, Gang Xiang
Departmental Technical Reports (CS)
Visualization Queries, Nicholas Del Rio, Paulo Pinheiro Da Silva
Visualization Queries, Nicholas Del Rio, Paulo Pinheiro Da Silva
Departmental Technical Reports (CS)
A New Answer To Pauli's Question: Almost All Quantum States Can Be Uniquely Determined By Measuring Location And Momentum, Don Jackson, Olga Kosheleva
A New Answer To Pauli's Question: Almost All Quantum States Can Be Uniquely Determined By Measuring Location And Momentum, Don Jackson, Olga Kosheleva
Departmental Technical Reports (CS)
Why L2 Topology In Quantum Physics, Chris Culellar, Evan Longpre, Vladik Kreinovich
Why L2 Topology In Quantum Physics, Chris Culellar, Evan Longpre, Vladik Kreinovich
Departmental Technical Reports (CS)
Cleanjava: A Formal Notation For Functional Program Verification, Yoonsik Cheon, Cesar Yeep, Melisa Vela
Cleanjava: A Formal Notation For Functional Program Verification, Yoonsik Cheon, Cesar Yeep, Melisa Vela
Departmental Technical Reports (CS)
Power Vs. Performance Evaluation Of Synthetic Aperture Radar ImageFormation Algorithms And Implementations For Embedded Hec Environments (Ongoing Study), Ricardo Portillo, Sarala Arunagiri, Patricia J. Teller
Power Vs. Performance Evaluation Of Synthetic Aperture Radar ImageFormation Algorithms And Implementations For Embedded Hec Environments (Ongoing Study), Ricardo Portillo, Sarala Arunagiri, Patricia J. Teller
Departmental Technical Reports (CS)
Towards Simpler Description Of Properties Like Commutativity And Associativity: Using Expression Fragments, Shubhra Datta, Valeria Fierro, Krasen Petrov, Jessica Romo, Gesuri Ramirez, Cesar Valenzuela
Towards Simpler Description Of Properties Like Commutativity And Associativity: Using Expression Fragments, Shubhra Datta, Valeria Fierro, Krasen Petrov, Jessica Romo, Gesuri Ramirez, Cesar Valenzuela
Departmental Technical Reports (CS)
Why Feynman Path Integration?, Jaime Nava, Juan Ferret, Vladik Kreinovich, Gloria Berumen, Sandra Griffin, Edgar Padilla
Why Feynman Path Integration?, Jaime Nava, Juan Ferret, Vladik Kreinovich, Gloria Berumen, Sandra Griffin, Edgar Padilla
Departmental Technical Reports (CS)
Expanding Algorithmic Randomness To The Algebraic Approach To Quantum Physics: Kolmogorov Complexity And Quantum Logics, Vladik Kreinovich
Expanding Algorithmic Randomness To The Algebraic Approach To Quantum Physics: Kolmogorov Complexity And Quantum Logics, Vladik Kreinovich
Departmental Technical Reports (CS)
Towards A Fast, Practical Alternative To Joint Inversion Of Multiple Datasets: Model Fusion, Omar Ochoa, Aaron A. Velasco, Christian Servin
Towards A Fast, Practical Alternative To Joint Inversion Of Multiple Datasets: Model Fusion, Omar Ochoa, Aaron A. Velasco, Christian Servin
Departmental Technical Reports (CS)
Datasets coming from different sources can provide complimentary information. In general, some of the datasets provide better accuracy and/or spatial resolution in some spatial areas and in some depths, while other datasets provide a better accuracy and/or spatial resolution in other areas or depths. For example: each gravity data points describes the result ...
Strings Lead To LatticeType Causality, Francisco Zapata, Essau Ramirez, Joel A. Lopez, Olga Kosheleva
Strings Lead To LatticeType Causality, Francisco Zapata, Essau Ramirez, Joel A. Lopez, Olga Kosheleva
Departmental Technical Reports (CS)
A Use CaseGuided Comparison Of Opm And Pml, Paulo Pinheiro Da Silva, Steve Roach
A Use CaseGuided Comparison Of Opm And Pml, Paulo Pinheiro Da Silva, Steve Roach
Departmental Technical Reports (CS)
Uncertainty In Partially Ordered Sets As A Natural Generalization Of Intervals: Negative Information Is Sufficient, Positive Is Not, David Mireles, Olga Kosheleva