scholarly journals Hedge Algebras: An Algebraic Approach to Domains of Linguistic Variables and Their Applicability

2017 ◽  
Vol 23 (1&2) ◽  
pp. 1
Author(s):  
Ho N.C. N.C.
Keyword(s):  
Inverted Pendulum ◽  
Algebraic Approach ◽  
Conditional Reasoning ◽  
Linguistic Variables ◽  
New Approach ◽  
Reasoning Problem ◽  
Fuzziness Measure ◽  
Linguistic Hedges

The paper is an overview on an algebraic approach to domains of linguistic variables and somefirst applications to show the applicability of this new approach. In this approach, each linguistic domain can be considered as a hedge algebra (HA for short) and based on the structure of HAs,a notion of fuzziness measure of linguistic hedges and terms can be defined. In order to apply hedge algebras to those problems, the results of which are needed, a notion of semantically quantifying mappings (SQMs) will be introduced. It shown that there is a closed connection between SQMs and fuzziness measure of hedge and primary terms (the generators of linguistic domains). To show the applicability of this approach, new met hods to solve a Fuzzy Multiple Conditional Reasoning problem, the problem of Balancing an Inverted Pendulum will be presented.

scholarly journals APPLICATION OF HEDGE ALGEBRAS FOR CONTROLLING MECHANISMS OF RELATIVE MANIPULATION

2017 ◽  
Vol 55 (5) ◽  
pp. 572
Author(s):  
Phan Bui Khoi ◽  
Nguyen Van Toan
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Controller ◽  
Complex Structure ◽  
Algebraic Approach ◽  
Linguistic Variables ◽  
Fuzzy Relations ◽  
Dynamical Equations ◽  
Linguistic Hedges ◽  
Linguistic Labels ◽  
Computed Torque

This paper presents a method for controlling mechanism of relative manipulation (MRM robot), that based on an algebraic approach to linguistic hedges in fuzzy logic. The proposed model of MRM robot is introduced as two component mechanisms, collaborating to realize technological manipulations. MRM robot has complex structure [1, [2]; therefore, robot system's  mathematical equations describing dynamical behaviors are complicated and voluminous [3,[4, 5]. Furthermore, the components affect MRM robot's dynamics that are difficult to determine adequately and exactly. Applying the well-known methods (based on dynamical equations) such as PD/PID, computed torque algorithm...for robot control is difficult, especially with MRM robot. By dint of the human-like inference mechanism, designing controller thanks to fuzzy logic can overcome the mentioned drawbacks [6]. However, the linguistic variables in fuzzy logic are not represented by any physical values; and hence, the comparison between the linguistic variables is unable. Moreover, composition of fuzzy relations, defuzzification use approximation function which can trigger error in data process. Hedge Algebras(HA) gives favorable conditions to restrict fuzzy logic's drawbacks because the linguistic labels in Hedge Algebras are represented by semantic values; and, composition of fuzzy relations and defuzzification are processed by simple interpolation and mapping functions. The obtained results from HA controller are compared to the obtained results from two methods which are presented in [6] (fuzzy controller and computed torque controller). Keywords: mechanism of relative manipulation (MRM robot), hedge algebras.

scholarly journals Conditional Reasoning

Management ◽  
2019 ◽  
Author(s):  
James M. LeBreton
Keyword(s):  
Measurement System ◽  
Inductive Reasoning ◽  
Indirect Measurement ◽  
Conditional Reasoning ◽  
Hostile Attribution Bias ◽  
Implicit Motives ◽  
Hostile Attribution ◽  
Reasoning Problem ◽  
Attribution Bias ◽  
Justification Mechanisms

Conditional reasoning refers to both a general theory of personality and an indirect measurement system used to assess personality. The basic tenets of the conditional reasoning theory of personality include: a) individuals’ wish to maintain a self-perception that their behavior is reasonable, logical, rational, and appropriate (versus unreasonable, illogical, irrational, and inappropriate); b) individuals with a strong implicit motive (desire or need) to pursue a behavior will develop biased patterns of reasoning that facilitates the conclusion that their behavior was indeed reasonable (i.e., logical, rational, appropriate); c) biases that serve to enhance the logical appeal of motive-based behaviors may be referred to as “justification mechanisms”; and d) distinct clusters or sets of justification mechanisms will be associated with each implicit motive. The basic tenets of the conditional reasoning measurement system include: a) it is possible to measure the extent to which justification mechanisms influence (i.e., bias) reasoning by asking individuals to solve inductive reasoning problems; b) individuals with stronger levels of the implicit motive (e.g., motive to aggress) will be more likely to select solutions to reasoning problems that are derived from the motive-relevant justification mechanisms (e.g., hostile attribution bias, retribution bias, derogation of target bias); and c) conditional reasoning is said to occur when the likelihood of judging a solution to an inductive reasoning problem as “correct” depends on the personality (i.e., the implicit motives and accompanying justification mechanisms) of the respondent.

An Intelligent Approach to Assess Tacit Knowledge Fitness in Networked Enterprises

2011 ◽  
Vol 2 (2) ◽  
pp. 1-18
Author(s):  
Khalid A. Al-Mutawah
Keyword(s):  
Tacit Knowledge ◽  
Linguistic Variables ◽  
Fuzzy Approach ◽  
New Approach ◽  
Partnership Formation ◽  
Neuro Fuzzy ◽  
Proposed Model ◽  
Assessment Approach ◽  
Intelligent Approach ◽  
Fuzzy Linguistic

Many organizations attempt to form strategic networked enterprises, yet such strategies are difficult to implement because they are as likely to fail as to succeed. This failure is due to intangible differences and mismatches between partners in tacit knowledge (TK). Despite the various proposed partnership assessment models/tools in the literature, an immediate need exists for a new approach to measure the mismatch in TK across different organizations. This is due to the complex, vague, and uncertain nature of TK attributes. Hence, an instrument for measuring vagueness (imprecise), such as fuzzy linguistic variables, is needed. In this study, the author applies a neuro-fuzzy approach to assess TK fitness in networked enterprises. The results show how differences in TK between partners affect the networked enterprise’s performance. Furthermore, the assessment approach reveals the most significant values to adopt and the irrelevant values that must be abandoned to smooth the partnership formation. The proposed model can prevent unexpected conflicts between partners if managed properly.

Parameterized complexity of abduction in Schaefer’s framework

2020 ◽  
Author(s):  
Yasir Mahmood ◽  
Arne Meier ◽  
Johannes Schmidt
Keyword(s):  
Constraint Satisfaction ◽  
Parameterized Complexity ◽  
Algebraic Approach ◽  
Abductive Reasoning ◽  
Fine Grained ◽  
Theory Of Computing ◽  
Reasoning Problem ◽  
Dimensional Classification ◽  
Complexity Classification

Abstract Abductive reasoning is a non-monotonic formalism stemming from the work of Peirce. It describes the process of deriving the most plausible explanations of known facts. Considering the positive version, asking for sets of variables as explanations, we study, besides the problem of wether there exists a set of explanations, two explanation size limited variants of this reasoning problem (less than or equal to, and equal to a given size bound). In this paper, we present a thorough two-dimensional classification of these problems: the first dimension is regarding the parameterized complexity under a wealth of different parameterizations, and the second dimension spans through all possible Boolean fragments of these problems in Schaefer’s constraint satisfaction framework with co-clones (T. J. Schaefer. The complexity of satisfiability problems. In Proceedings of the 10th Annual ACM Symposium on Theory of Computing, May 1–3, 1978, San Diego, California, USA, R.J. Lipton, W.A. Burkhard, W.J. Savitch, E.P. Friedman, A.V. Aho eds, pp. 216–226. ACM, 1978). Thereby, we almost complete the parameterized complexity classification program initiated by Fellows et al. (The parameterized complexity of abduction. In Proceedings of the Twenty-Sixth AAAI Conference on Articial Intelligence, July 22–26, 2012, Toronto, Ontario, Canada, J. Homann, B. Selman eds. AAAI Press, 2012), partially building on the results by Nordh and Zanuttini (What makes propositional abduction tractable. Artificial Intelligence, 172, 1245–1284, 2008). In this process, we outline a fine-grained analysis of the inherent parameterized intractability of these problems and pinpoint their FPT parts. As the standard algebraic approach is not applicable to our problems, we develop an alternative method that makes the algebraic tools partially available again.

Linguistic dynamic simulation A new approach

SIMULATION ◽  
1987 ◽  
Vol 49 (5) ◽  
pp. 208-212 ◽  
Author(s):  
António S. Câmara ◽  
Paula C. Antunes ◽  
Manuel Duarte Pinheiro ◽  
Maria Julia Fonseca de Seixas
Keyword(s):  
Structural Change ◽  
Dynamic Simulation ◽  
Linguistic Variables ◽  
High Level Language ◽  
New Approach ◽  
Modeling Methodology ◽  
Potential Applications ◽  
High Level ◽  
Logical Rules ◽  
Very High

A new dynamic modeling methodology, SLIN, allows for the analysis of systems defined by linguistic variables. SLIN applies a set of logical rules which include base, tactical, strategic and structural change. To make the transition from qualitative to quantitative modes, logical rules are also used. SLIN is advanta geously implemented in a very high-level language such as PRO LOG. A simple ecological modeling problem illustrates SLIN's potential applications.

Some Maclaurin Symmetric Mean Aggregation Operators Based on Cloud Model and Their Application to Decision-Making

2019 ◽  
Vol 18 (03) ◽  
pp. 981-1007 ◽  
Author(s):  
Peide Liu ◽  
Hongyu Yang ◽  
Haiquan Wu ◽  
Meilong Ju ◽  
Fawaz E. Alsaadi
Keyword(s):  
Decision Making ◽  
Quantitative Method ◽  
Group Decision ◽  
Cloud Model ◽  
Aggregation Operators ◽  
Linguistic Variables ◽  
Qualitative Information ◽  
New Approach ◽  
Maclaurin Symmetric Mean ◽  
Magdm Problems

The cloud model (CM) is an important tool to describe qualitative concept by the quantitative method, and the Maclaurin symmetric mean (MSM) can capture the interrelationship among the multi-inputs and it can generalize most of existing operators. In this paper, we firstly convert the uncertain linguistic variables (ULVs), which are easily used to express the qualitative information, to CM. Then, we combine the MSM with the CM, and propose the cloud MSM (CMSM) operator and cloud weighted MSM (CWMSM) operator. In addition, we explore some of their desirable features and develop a new approach to deal with some multi-attribute group decision-making (MAGDM) problems under the uncertain environment based on the proposed operators. Finally, by comparing with other approaches, an illustrative example is arranged to demonstrate the usability of the proposed method.

A NEW APPROACH TO LEARNING LINGUISTIC CONTROL RULES

2000 ◽  
Vol 08 (01) ◽  
pp. 21-43 ◽  
Author(s):  
J. F. BALDWIN ◽  
J. LAWRY
Keyword(s):  
Rule Base ◽  
Linguistic Variables ◽  
Data Set ◽  
New Approach ◽  
Approach To Learning ◽  
Control Rules ◽  
System A ◽  
Id3 Algorithm ◽  
On Line ◽  
Linguistic Control

The mass assignment ID3 (MA-ID3) algorithm for generating linguistic decision trees is introduced together with the mass assignment semantics for linguistic variables. The potential of this algorithm for learning control rules is illustrated by means of the Van de Pol system. A data set of control paths is generated using an existing on-line controller. This is then used to generate a set of quantified linguistic control rules. The effectiveness and robustness of this rule-base is then demonstrated.

scholarly journals Algebraic Theory of Molecules

1995 ◽  
Author(s):  
F. Iachello ◽  
R. D. Levine
Keyword(s):  
Quantum Mechanics ◽  
Molecular Spectroscopy ◽  
Algebraic Theory ◽  
Algebraic Approach ◽  
Geometric Approach ◽  
Wave Functions ◽  
New Approach ◽  
Geometric Methods ◽  
The Relationship ◽  
Basic Level

Algebraic Theory of Molecules presents a fresh look at the mathematics of wave functions that provide the theoretical underpinnings of molecular spectroscopy. Written by renowned authorities in the field, the book demonstrates the advantages of algebraic theory over the more conventional geometric approach to developing the formal quantum mechanics inherent in molecular spectroscopy. Many examples are provided that compare the algebraic and geometric methods, illustrating the relationship between the algebraic approach and current experiments. The authors develop their presentation from a basic level so as to enable newcomers to enter the field while providing enough details and concrete examples to serve as a reference for the expert. Chemical physicists, physical chemists, and spectroscopists will want to read this exciting new approach to molecular spectroscopy.

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