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Practical use of fuzzy implicative gradual rules in knowledge representation and comparison with Mamdani rules

Hazaël Jones, Serge Guillaume, Brigitte Charnomordic, Didier Dubois
2005 European Society for Fuzzy Logic and Technology  
Nevertheless, fuzzy implicative rules, and especially gradual rules, provide another kind of knowledge representation, which can be very useful in approximate reasoning.  ...  Finally, we discuss the complemental aspects of these rules and we show how in certain cases gradual rules may constitute an interesting alternative to Mamdani rules.  ...  Implicative gradual rules Implicative rules are a straightforward application of Zadeh's theories [8] of approximate reasoning.  ... 
dblp:conf/eusflat/JonesGCD05 fatcat:cnap5m23argzbe6c2sguiji2wq

A practical inference method with several implicative gradual rules and a fuzzy input: one and two dimensions

Hazael Jones, Didier Dubois, Serge Guillaume, Brigitte Charnomordic
2007 IEEE International Fuzzy Systems conference proceedings  
A general approach to practical inference with gradual implicative rules and fuzzy inputs is presented. Gradual rules represent constraints restricting outputs of a fuzzy system for each input.  ...  A double decomposition of fuzzy inputs is done in terms of α-cuts and in terms of a partitioning of these cuts according to areas where only a few rules apply.  ...  There are different kinds of implicative rules: certainty rules and gradual rules. In this article, we only focus on gradual rules.  ... 
doi:10.1109/fuzzy.2007.4295462 dblp:conf/fuzzIEEE/JonesDGC07 fatcat:7kfzlzng5bdtbnxzd7aqbl5oiq

Approximate reasoning by linear rule interpolation and general approximation

LászlóT. Kóczy, Kaoru Hirota
1993 International Journal of Approximate Reasoning  
Graduality, measurability, and distance in the fuzzy sense are introduced.  ...  Various methods of analogical reasoning available in the literature are reviewed.  ...  Gradual reasoning based on gradual rules can be applied whenever the input and output variables are gradual.  ... 
doi:10.1016/0888-613x(93)90010-b fatcat:b5syfq2mijc7rffhnd4rhiwio4

Representing Imprecise Time Intervals in OWL 2

Elisabeth Métais, Fatma Ghorbel, Fayçal Hamdi, Nebrasse Ellouze, Noura Herradi, Assia Soukane
2018 Enterprise Modelling and Information Systems Architectures - An International Journal  
The Allen's interval algebra is extended in order to compare imprecise time intervals in a fuzzy gradual personalized way. Inferences are done via a set of Mamdani IF-THEN rules.  ...  Then, we extend the Allen's interval algebra to compare imprecise time intervals in a crisp way and inferences are done via a set of SWRL rules. (2) The second approach is based on fuzzy sets theory and  ...  Furthermore he also never lost his kindness and humanity in spite of being one of the greatest researchers in Europe.  ... 
doi:10.18417/emisa.si.hcm.11 dblp:journals/emisaij/MetaisGHEHS18 fatcat:loamvwoyvnglpolmy2gezkfnlm

Gradual Machine Learning for Entity Resolution [article]

Boyi Hou, Qun Chen, Yanyan Wang, Youcef Nafa, Zhanhuai Li
2019 arXiv   pre-print
It begins with some easy instances in a task, which can be automatically labeled by the machine with high accuracy, and then gradually labels more challenging instances by iterative factor graph inference  ...  In gradual machine learning, the hard instances in a task are gradually labeled in small stages based on the estimated evidential certainty provided by the labeled easier instances.  ...  The unsupervised rule-based approach reasons about pair equivalence based on the rules handcrafted by the human.  ... 
arXiv:1810.12125v4 fatcat:bo7kmdgprjd7fh6wd2uikxedsu

Practical Inference With Systems of Gradual Implicative Rules

H. Jones, B. Charnomordic, D. Dubois, S. Guillaume
2009 IEEE transactions on fuzzy systems  
A general approach to practical inference with gradual implicative rules and fuzzy inputs is presented. Gradual rules represent constraints restricting outputs of a fuzzy system for each input.  ...  A double decomposition of fuzzy inputs is done in terms of α-cuts and in terms of a partitioning of these cuts according to areas where only a few rules apply.  ...  The approximated output contains the true output. It could be interesting to keep both inner and external approximations in order to reason with two approximations like for Rough Sets [31] .  ... 
doi:10.1109/tfuzz.2008.2007851 fatcat:qtiieqlvcfcgbihu5c5aajvtlu

Casts and costs: harmonizing safety and performance in gradual typing

John Peter Campora, Sheng Chen, Eric Walkingshaw
2018 Proceedings of the ACM on Programming Languages  
To address these problems, we develop: (1) a static cost semantics that accurately predicts the overhead of static-dynamic interactions in a gradually typed program, (2) a technique for efficiently inferring  ...  Gradual typing allows programmers to use both static and dynamic typing in a single program.  ...  We simply infer types for as many parameters as possible, then reason about this space of migrations.  ... 
doi:10.1145/3236793 dblp:journals/pacmpl/Campora0W18 fatcat:uohvlrc6pzgqdpmrqjlf35wmgq

Gradual Generalized Modus Ponens

Phuc-Nguyen Vo, Marcin Detyniecki, Bernadette Bouchon-Meunier
2013 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)  
Gradual relationship between premises and conclusions is often an underlying property of fuzzy rules.  ...  In this paper, we propose to integrate the gradual hypothesis, sometimes called monotonicity, to Generalized Modus Ponens (GMP).  ...  GENERALIZED MODUS PONENS Generalized Modus Ponens is a key inferring mechanism in approximate reasoning. Let X and Y be two variables in the universes of discourse U and V .  ... 
doi:10.1109/fuzz-ieee.2013.6622520 dblp:conf/fuzzIEEE/VoDB13 fatcat:f45amz2xs5dlhfdmrs74ujr54e

Advances in fuzzy sets and rough sets

Francesco Masulli, Alfredo Petrosino
2006 International Journal of Approximate Reasoning  
In the former, Fuzzy rough sets and multiple-premise gradual decision rules, Greco et al. present a new fuzzy rough set approach able to infer the most cautious conclusions from available imprecise information  ...  The third, A Rough Set-Based Case-Based Reasoner for Text Categorization, by Li et al. presents a novel case-based reasoner for text categorization that operates by first reducing the number of feature  ... 
doi:10.1016/j.ijar.2005.06.010 fatcat:iuth23adurflvojigc346dg6pa

Page 409 of Mathematical Reviews Vol. , Issue 93a [page]

1993 Mathematical Reviews  
(F-TOUL3-IR) Gradual inference rules in approximate reasoning.  ...  This representation turns out to be based on a special implication function already considered in multiple-valued logic. Patterns of reasoning involving gradual inference rules are formalized.  ... 

Qualitative reasoning based on fuzzy relative orders of magnitude

A.H. Ali, D. Dubois, H. Prade
2003 IEEE transactions on fuzzy systems  
A set of sound inference rules, involving the tolerance parameters, is provided, in full accordance with the combination/projection principle underlying the approximate reasoning method of Zadeh.  ...  The effect of the chaining of rules in the inference process can be controlled through the gradual deterioration of closeness and negligibility relations involved in the produced conclusions.  ...  SYMMETRIC APPROXIMATIONS OF INFERENCE RULES In the inference rules of section 4, some tolerance parameters underlying the relations appearing in conclusion parts are expressed in complex, hence unwieldy  ... 
doi:10.1109/tfuzz.2002.806313 fatcat:uvhd3lqju5ap3d6ebsp6lsdpke

Incorporating the Basic Elements of a First-degree Fuzzy Logic and Certain Elments of Temporal Logic for Dynamic Management Applications

Vasile MAZILESCU
2010 Annals of Dunarea de Jos University. Fascicle I : Economics and Applied Informatics  
The approximate reasoning is perceived as a derivation of new formulas with the corresponding temporal attributes, within a fuzzy theory defined by the fuzzy set of special axioms.  ...  In this kind of situations it is necessary to elaborate certain mechanisms in order to maintain the coherence of the obtained conclusions, to figure out their degree of reliability and thetime domain for  ...  The conclusions of the paper appear in Section 4. Approximate Reasoning Modeling The approximate reasoning refers to creating new rules of inference and translation.  ... 
doaj:d11babb5b84d4f99a06819200d02fa89 fatcat:xc6l5tq6rbh6znxq4bydgdkssa

A data-driven approximate causal inference model using the evidential reasoning rule

Yue Chen, Yu-Wang Chen, Xiao-Bin Xu, Chang-Chun Pan, Jian-Bo Yang, Gen-Ke Yang
2015 Knowledge-Based Systems  
This paper aims to develop a data-driven approximate causal inference model using the newly-proposed evidential reasoning (ER) rule.  ...  The ER rule constitutes a generic conjunctive probabilistic reasoning process and generalises Dempster's rule and Bayesian inference.  ...  In Section 3, an approximate causal inference model using the ER rule is explored in view of data-based causal modelling and optimal learning.  ... 
doi:10.1016/j.knosys.2015.07.026 fatcat:33or22xl3zdszlvgtwwbep3iye

Different Conceptions of Learning: Function Approximation vs. Self-Organization [chapter]

Pei Wang, Xiang Li
2016 Lecture Notes in Computer Science  
This paper compares two understandings of "learning" in the context of AGI research: algorithmic learning that approximates an input/output function according to given instances, and inferential learning  ...  The former is how "learning" is often interpreted in the machine learning community, while the latter is exemplified by the AGI system NARS.  ...  The only knowledge that cannot be learned is the meta-knowledge embedded in the system's grammar rules, inference rules, resources management policy, etc.  ... 
doi:10.1007/978-3-319-41649-6_14 fatcat:jlivlzppdzfqnfotvwhyvbq44e

A new approach to fuzzy reasoning

J. Weisbrod
1998 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
For a fuzzy rule base, that maximizes completeness at the cost of consistency, we derive a new type of inference called {reasoning.  ...  Together, both mechanisms form an embracing theory for fuzzy reasoning in general. We propose a combined approach to be applied in order to manage complex rule bases.  ...  II Fuzzy Reasoning Fuzzy or approximate reasoning deals with the formalization and activation of rule based knowledge that is based on vague predicates.  ... 
doi:10.1007/s005000050037 fatcat:cm4jnorqxzbuvin67iwntce73m
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