[33] **viXra:1003.0257 [pdf]**
*submitted on 8 Mar 2010*

**Authors:** Florentin Smarandache

**Comments:** 26 pages

In this paper we introduce a new procedure called α-Discounting Method for
Multi-Criteria Decision Making (α-D MCDM), which is as an alternative and extension of
Saaty's Analytical Hierarchy Process (AHP). It works for any set of preferences that can
be transformed into a system of homogeneous linear equations. A degree of consistency
(and implicitly a degree of inconsistency) of a decision-making problem are defined. α-D
MCDM is generalized to a set of preferences that can be transformed into a system of
linear and/or non-linear homogeneous and/or non-homogeneous equations and/or
inequalities.
Many consistent, weak inconsistent, and strong inconsistent examples are given.

**Category:** Artificial Intelligence

[32] **viXra:1003.0252 [pdf]**
*replaced on 2013-04-22 14:06:13*

**Authors:** Modris Tenisons, Dainis Zeps

**Comments:** 19 Pages. Corrected version

We consider an ornamental sign language of first order where principles of sieve displacement, of asymmetric building blocks as a base of ornament symmetry, color exchangeability and side equivalence principles work. Generic aspects of sieve and a genesis of ornamental pattern and ornament signs in it are discussed. Hemiolia principle for ornamental genesis is introduced. The discoverer of most of these principles were artist Modris Tenisons [4, 5, 6, 7 (refs. 23, 24), 8 (ref. 65)]. Here we apply a systematical research using simplest mathematical arguments.
We come to conclusions that mathematical argument in arising ornament is of much more significance than simply symmetries in it as in an image. We are after to inquire how ornament arises from global aspects intertwined with these local. We raise an argument of sign’s origin from code rather from image, and its eventual impact on research of ornamental patterns, and on research of human prehension of sign and its connection with consciousness.

**Category:** Artificial Intelligence

[31] **viXra:1003.0232 [pdf]**
*submitted on 7 Mar 2010*

**Authors:** W. B. Vasantha Kandasamy, Florentin Smarandache

**Comments:** 213 pages

In a world of chaotic alignments, traditional logic with its strict boundaries of truth
and falsity has not imbued itself with the capability of reflecting the reality. Despite
various attempts to reorient logic, there has remained an essential need for an
alternative system that could infuse into itself a representation of the real world. Out
of this need arose the system of Neutrosophy, and its connected logic, Neutrosophic
Logic. Neutrosophy is a new branch of philosophy that studies the origin, nature and
scope of neutralities, as well as their interactions with different ideational spectra.
This was introduced by one of the authors, Florentin Smarandache. A few of the
mentionable characteristics of this mode of thinking are [90-94]: It proposes new
philosophical theses, principles, laws, methods, formulas and movements; it reveals
that the world is full of indeterminacy; it interprets the uninterpretable; regards, from
many different angles, old concepts, systems and proves that an idea which is true in
a given referential system, may be false in another, and vice versa; attempts to make
peace in the war of ideas, and to make war in the peaceful ideas! The main principle
of neutrosophy is: Between an idea and its opposite

**Category:**

[30] **viXra:1003.0209 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 461 pages

This second book devoted on advances and applications of Dezert-Smarandache Theory
(DSmT) for information fusion collects recent papers from different researchers working in
engineering and mathematics. Part 1 of this book presents the current state-of-the-art on theoretical
investigations while, Part 2 presents several applications of this new theory. Some ideas
in this book are still under current development or improvements, but we think it is important
to propose them in order to share ideas and motivate new debates with people interested in
new reasoning methods and information fusion. So, we hope that this second volume on DSmT
will continue to stir up some interests to researchers and engineers working in data fusion and
in artificial intelligence.

**Category:** Artificial Intelligence

[29] **viXra:1003.0208 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 438 pages

This book is devoted to an emerging branch of Information Fusion based on new approach for modelling
the fusion problematic when the information provided by the sources is both uncertain and
(highly) conflicting. This approach, known in literature as DSmT (standing for Dezert-Smarandache
Theory), proposes new useful rules of combinations. We gathered in this volume a presentation of DSmT
from the beginning to the latest development. Part 1 of this book presents the current state-of-the-art on
theoretical investigations while Part 2 presents several applications of this new theory. We hope that this
first book on DSmT will stir up some interests to researchers and engineers working in data fusion and in
artificial intelligence. Many simple but didactic examples are proposed throughout the book. As a young
emerging theory, DSmT is probably not exempt from improvements and its development will continue to
evolve over the years. We just want through this book to propose a new look at the Information Fusion
problematic and open a new track to attack the combination of information.

**Category:** Artificial Intelligence

[28] **viXra:1003.0197 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Aloïs Kirchnera, Frédéric Dambrevilleb, Francis Celeste, Florentin Smarandache, Jean Dezert

**Comments:** 9 pages

This paper defines and implements a non-Bayesian
fusion rule for combining densities of probabilities estimated
by local (non-linear) filters for tracking a moving target by
passive sensors. This rule is the restriction to a strict probabilistic
paradigm of the recent and efficient Proportional Conflict Redistribution
rule no 5 (PCR5) developed in the DSmT framework
for fusing basic belief assignments. A sampling method for
probabilistic PCR5 (p-PCR5) is defined. It is shown that
p-PCR5 is more robust to an erroneous modeling and allows to
keep the modes of local densities and preserve as much as
possible the whole information inherent to each densities to
combine. In particular, p-PCR5 is able of maintaining multiple
hypotheses/modes after fusion, when the hypotheses are too
distant in regards to their deviations. This new p-PCR5 rule has
been tested on a simple example of distributed non-linear filtering
application to show the interest of such approach for future
developments. The non-linear distributed filter is implemented
through a basic particles filtering technique. The results obtained
in our simulations show the ability of this p-PCR5-based filter
to track the target even when the models are not well consistent
in regards to the initialization and real cinematic.
Keywords: Filtering, Robust estimation, non-Bayesian fusion
rule, PCR5, Particle filtering.

**Category:** Artificial Intelligence

[27] **viXra:1003.0196 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 13 pages

In this paper we extend the new family of (quantitative) Belief Conditioning Rules (BCR) recently
developed in the Dezert-Smarandache Theory (DSmT) to their qualitative counterpart for belief revision. Since
the revision of quantitative as well as qualitative belief assignment given the occurrence of a new event (the
conditioning constraint) can be done in many possible ways, we present here only what we consider as the most
appealing Qualitative Belief Conditioning Rules (QBCR) which allow to revise the belief directly with words and
linguistic labels and thus avoids the introduction of ad-hoc translations of quantitative beliefs into quantitative
ones for solving the problem.

**Category:** Artificial Intelligence

[26] **viXra:1003.0195 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Xin-De Li, Xinhan Huang, Florentin Smarandache, Jean Dezert

**Comments:** 12 pages

This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for
combining information expressed in natural language through linguistic labels. In this work, two possible enrichments
(quantitative and/or qualitative) of linguistic labels are considered and operators (addition, multiplication,
division, etc) for dealing with them are proposed and explained. We denote them qe-operators, qe standing for
"qualitative-enriched" operators. These operators can be seen as a direct extension of the classical qualitative
operators (q-operators) proposed recently in the Dezert-Smarandache Theory of plausible and paradoxist reasoning
(DSmT). q-operators are also justified in details in this paper. The quantitative enrichment of linguistic label
is a numerical supporting degree in [0,∞), while the qualitative enrichment takes its values in a finite ordered
set of linguistic values. Quantitative enrichment is less precise than qualitative enrichment, but it is expected
more close with what human experts can easily provide when expressing linguistic labels with supporting degrees.
Two simple examples are given to show how the fusion of qualitative-enriched belief assignments can be done.

**Category:** Artificial Intelligence

[25] **viXra:1003.0181 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 41 pages

In this paper we propose five versions of a Proportional Conflict Redistribution rule (PCR) for information fusion together
with several examples. From PCR1 to PCR2, PCR3, PCR4, PCR5 one increases the complexity of the rules and also the exactitude
of the redistribution of conflicting masses. PCR1 restricted from the hyper-power set to the power set and without degenerate cases
gives the same result as the Weighted Average Operator (WAO) proposed recently by Jøsang, Daniel and Vannoorenberghe but does
not satisfy the neutrality property of vacuous belief assignment. That's why improved PCR rules are proposed in this paper. PCR4 is
an improvement of minC and Dempster's rules. The PCR rules redistribute the conflicting mass, after the conjunctive rule has been
applied, proportionally with some functions depending on the masses assigned to their corresponding columns in the mass matrix.
There are infinitely many ways these functions (weighting factors) can be chosen depending on the complexity one wants to deal with
in specific applications and fusion systems. Any fusion combination rule is at some degree ad-hoc.

**Category:** Artificial Intelligence

[24] **viXra:1003.0174 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jose L. Salmeron, Florentin Smarandache

**Comments:** 12 pages

For academics and practitioners concerned with computers, business and
mathematics, one central issue is supporting decision makers. In this paper, we
propose a generalization of Decision Matrix Method (DMM), using Neutrosophic
logic. It emerges as an alternative to the existing logics and it represents a
mathematical model of uncertainty and indeterminacy. This paper proposes the
Neutrosophic Decision Matrix Method as a more realistic tool for decision
making. In addition, a de-neutrosophication process is included.

**Category:** Artificial Intelligence

[23] **viXra:1003.0165 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Haibin Wang, André Rogatko, Florentin Smarandache, Rajshekhar Sunderraman

**Comments:** 19 pages

Description Logics (DLs) are appropriate, widely used, logics for managing structured
knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals
with common properties. Typically, DLs are limited to dealing with crisp, well defined
concepts. That is, concepts for which the problem whether an individual is an instance of
it is a yes/no question. More often than not, the concepts encountered in the real world do
not have a precisely defined criteria of membership: we may say that an individual is an
instance of a concept only to a certain degree, depending on the individual's properties.
The DLs that deal with such fuzzy concepts are called fuzzy DLs. In order to deal
with fuzzy, incomplete, indeterminate and inconsistent concepts, we need to extend the
capabilities of fuzzy DLs further.
In this paper we will present an extension of fuzzy ALC, combining Smarandache's
neutrosophic logic with a classical DL. In particular, concepts become neutrosophic (here
neutrosophic means fuzzy, incomplete, indeterminate and inconsistent), thus, reasoning
about such neutrosophic concepts is supported. We will define its syntax, its semantics,
describe its properties and present a constraint propagation calculus for reasoning in it.

**Category:** Artificial Intelligence

[22] **viXra:1003.0161 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache

**Comments:** 11 pages

The management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of
information has always been and still remains of primal importance for the development of reliable information fusion systems.
In this short survey paper, we present the theory of plausible and paradoxical reasoning, known as DSmT (Dezert-Smarandache
Theory) in literature, developed for dealing with imprecise, uncertain and potentially highly conflicting sources of information.
DSmT is a new paradigm shift for information fusion and recent publications have shown the interest and the potential ability
of DSmT to solve fusion problems where Dempster's rule used in Dempster-Shafer Theory (DST) provides counter-intuitive
results or fails to provide useful result at all. This paper is focused on the foundations of DSmT and on its main rules of combination
(classic, hybrid and Proportional Conflict Redistribution rules). Shafer's model on which is based DST appears as a
particular and specific case of DSm hybrid model which can be easily handled by DSmT as well. Several simple but illustrative
examples are given throughout this paper to show the interest and the generality of this new theory.

**Category:** Artificial Intelligence

[21] **viXra:1003.0159 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 21 pages

The management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of
information has always been, and still remains today, of primal importance for the development of reliable modern information systems
involving artificial reasoning. In this introduction, we present a survey of our recent theory of plausible and paradoxical reasoning,
known as Dezert-Smarandache Theory (DSmT) in the literature, developed for dealing with imprecise, uncertain and paradoxical
sources of information. We focus our presentation here rather on the foundations of DSmT, and on the two important new rules of
combination, than on browsing specific applications of DSmT available in literature. Several simple examples are given throughout the
presentation to show the efficiency and the generality of this new approach.

**Category:** Artificial Intelligence

[20] **viXra:1003.0157 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 13 pages

This paper introduces the notion of qualitative belief assignment to model beliefs of human experts
expressed in natural language (with linguistic labels). We show how qualitative beliefs can be efficiently combined
using an extension of Dezert-Smarandache Theory (DSmT) of plausible and paradoxical quantitative reasoning
to qualitative reasoning. We propose a new arithmetic on linguistic labels which allows a direct extension of
classical DSm fusion rule or DSm Hybrid rules. An approximate qualitative PCR5 rule is also proposed jointly
with a Qualitative Average Operator. We also show how crisp or interval mappings can be used to deal indirectly
with linguistic labels. A very simple example is provided to illustrate our qualitative fusion rules.

**Category:** Artificial Intelligence

[19] **viXra:1003.0156 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Albena Tchamova, Florentin Smarandache, Pavlina Konstantinova

**Comments:** 10 pages

In this paper we consider and analyze the behavior of two combinational rules for temporal (sequential)
attribute data fusion for target type estimation. Our comparative analysis is based on Dempster's
fusion rule proposed in Dempster-Shafer Theory (DST) and on the Proportional Conflict Redistribution rule no.
5 (PCR5) recently proposed in Dezert-Smarandache Theory (DSmT). We show through very simple scenario
and Monte-Carlo simulation, how PCR5 allows a very efficient Target Type Tracking and reduces drastically the
latency delay for correct Target Type decision with respect to Demspter's rule. For cases presenting some short
Target Type switches, Demspter's rule is proved to be unable to detect the switches and thus to track correctly
the Target Type changes. The approach proposed here is totally new, efficient and promising to be incorporated
in real-time Generalized Data Association - Multi Target Tracking systems (GDA-MTT) and provides an important
result on the behavior of PCR5 with respect to Dempster's rule. The MatLab source code is provided in
[5].

**Category:** Artificial Intelligence

[18] **viXra:1003.0155 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jose L. Salmeron, Florentin Smarandache

**Comments:** 13 pages

IS projects success is a complex concept, and its evaluation is complicated, unstructured
and not readily quantifiable. Numerous scientific publications address the issue of
success in the IS field as well as in other fields. But, little efforts have been done for
processing indeterminacy and uncertainty in success research. This paper shows a
formal method for mapping success using Neutrosophic Success Map. This is an
emerging tool for processing indeterminacy and uncertainty in success research. EIS
success have been analyzed using this tool.

**Category:** Artificial Intelligence

[17] **viXra:1003.0154 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 20 pages

The management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of
information has always been, and still remains today, of primal importance for the development of reliable modern information systems
involving artificial reasoning. In this chapter, we present a survey of our recent theory of plausible and paradoxical reasoning, known
as Dezert-Smarandache Theory (DSmT) in the literature, developed for dealing with imprecise, uncertain and paradoxical sources of
information. We focus our presentation here rather on the foundations of DSmT, and on the two important new rules of combination,
than on browsing specific applications of DSmT available in literature. Several simple examples are given throughout the presentation
to show the efficiency and the generality of this new approach. The last part of this chapter concerns the presentation of the neutrosophic
logic, the neutro-fuzzy inference and its connection with DSmT. Fuzzy logic and neutrosophic logic are useful tools in decision making
after fusioning the information using the DSm hybrid rule of combination of masses.

**Category:** Artificial Intelligence

[16] **viXra:1003.0152 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache, Milan Daniel

**Comments:** 11 pages

This paper presents in detail the generalized pignistic transformation (GPT) succinctly developed in the Dezert-Smarandache
Theory (DSmT) framework as a tool for decision process. The GPT allows to provide a subjective probability measure from any generalized
basic belief assignment given by any corpus of evidence. We mainly focus our presentation on the 3D case and provide the
complete result obtained by the GPT and its validation drawn from the probability theory.

**Category:** Artificial Intelligence

[15] **viXra:1003.0150 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache

**Comments:** 17 pages

In this paper, one studies the famous well-known and challenging Tweety Penguin Triangle Problem (TPTP or TP2)
pointed out by Judea Pearl in one of his books. We first present the solution of the TP2 based on the fallacious Bayesian reasoning and
prove that reasoning cannot be used to conclude on the ability of the penguin-bird Tweety to fly or not to fly. Then we present in details
the counter-intuitive solution obtained from the Dempster-Shafer Theory (DST). Finally, we show how the solution can be obtained
with our new theory of plausible and paradoxical reasoning (DSmT)

**Category:** Artificial Intelligence

[14] **viXra:1003.0149 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache

**Comments:** 13 pages

This paper presents several classes of fusion problems which cannot be directly attacked by the classical mathematical
theory of evidence, also known as the Dempster-Shafer Theory (DST) either because the Shafer's model for the frame of discernment
is impossible to obtain or just because the Dempster's rule of combination fails to provide coherent results (or no result at all). We
present and discuss the potentiality of the DSmT combined with its classical (or hybrid) rule of combination to attack these infinite
classes of fusion problems.

**Category:** Artificial Intelligence

[13] **viXra:1003.0148 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache

**Comments:** 33 pages

This paper presents a general method for combining uncertain and paradoxical source of evidences
for a wide class of fusion problems. From the foundations of the Dezert-Smarandache Theory (DSmT) we show
how the DSm rule of combination can be adapted to take into account all possible integrity constraints (if any)
of the problem under consideration due to the true nature of elements/concepts involved into it. We show how
the Shafer's model can be considered as a specific DSm hybrid model and be easily handled by our approach and
a new efficient rule of combination different from the Dempster's rule is obtained. Several simple examples are
also provided to show the efficiency and the generality of the approach proposed in this work.

**Category:** Artificial Intelligence

[12] **viXra:1003.0147 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache

**Comments:** 11 pages

The recent theory of plausible and paradoxical reasoning (DSmT) developed by the authors appears
to be a nice promising theoretical tools to solve many information fusion problems where the Shafer's model
cannot be used due to the intrinsic paradoxical nature of the elements of the frame of discernment and where
a strong internal conflict between sources arises. The main idea of DSmT is to work on the hyper-powerset of
the frame of discernment of the problem under consideration. Although the definition of hyper-powerset is well
established, the major difficulty in practice is to generate such hyper-powersets in order to implement DSmT
fusion rule on computers. We present in this paper a simple algorithm for generating hyper-powersets and
discuss the limitations of our actual computers to generate such hyper-powersets when the dimension of the
problem increases.

**Category:** Artificial Intelligence

[11] **viXra:1003.0146 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache

**Comments:** 13 pages

In this paper, we examine several issues for ordering or partially ordering elements of hyperpowertsets
involved in the recent theory of plausible, uncertain and paradoxical reasoning (DSmT) developed by
the authors. We will show the benefit of some of these issues to obtain a nice and useful matrix representation
of belief functions.

**Category:** Artificial Intelligence

[10] **viXra:1003.0114 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache

**Comments:** 30 pages

In this article one investigates Rugina's Orientation Table and one gives particular examples for
several of its seven models.
Leon Walras's Economics of Stable Equilibrium and Keynes's Economics of Disequilibrium are combined in
Rugina's Orientation Table in systems which are s% stable and 100-s% unstable, where s may be 100, 95, 65,
50, 35, 5, and 0.
The Classical Logic and Modern Logic are united in Rugina's Integrated Logic, and then generalized in the
Neutrosophic Logic.

**Category:** Artificial Intelligence

[9] **viXra:1003.0110 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Arnaud Martin, Florentin Smarandache

**Comments:** 5 pages

Comments on "A new combination of evidence based on compromise"

**Category:** Artificial Intelligence

[8] **viXra:1003.0108 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Mark Alford

**Comments:** 9 pages

In this paper we introduce two new DSm fusion conditioning rules with example, and as
a generalization of them a class of DSm fusion conditioning rules, and then extend them
to a class of DSm conditioning rules.

**Category:** Artificial Intelligence

[7] **viXra:1003.0101 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Albena Tchamova, Jean Dezert, Florentin Smarandache

**Comments:** 6 pages

This paper presents a new approach for solving
the paradoxical Blackman's Association Problem. It utilizes
the recently defined new class fusion rule based on fuzzy Tconorm/
T-norm operators together with Dezert-Smarandache theory
based, relative variations of generalized
pignistic probabilities measure of correct associations,
defined from a partial ordering function of hyper-power set.
The ability of this approach to solve the problem against the
classical Dempster-Shafer's method, proposed in the
literature is proven. It is shown that the approach improves
the separation power of the decision process for this
association problem.

**Category:** Artificial Intelligence

[6] **viXra:1003.0100 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Jean Dezert, Florentin Smarandache, Albena Tchamova

**Comments:** 11 pages

Modern multitarget-multisensor tracking systems involve the development of reliable methods for
the data association and the fusion of multiple sensor information, and more specifically the partioning of
observations into tracks. This paper discusses and compares the application of Dempster-Shafer Theory (DST)
and the Dezert-Smarandache Theory (DSmT) methods to the fusion of multiple sensor attributes for target
identification purpose. We focus our attention on the paradoxical Blackman's association problem and propose
several approaches to outperfom Blackman's solution. We clarify some preconceived ideas about the use of degree
of conflict between sources as potential criterion for partitioning evidences.

**Category:** Artificial Intelligence

[5] **viXra:1003.0094 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Florentin Smarandache, Jean Dezert

**Comments:** 27 pages

In this paper we propose a new family of Belief Conditioning Rules (BCR) for belief revision.
These rules are not directly related with the fusion of several sources of evidence but with the revision of a belief
assignment available at a given time according to the new truth (i.e. conditioning constraint) one has about the
space of solutions of the problem.

**Category:** Artificial Intelligence

[4] **viXra:1003.0083 [pdf]**
*submitted on 5 Mar 2010*

**Authors:** M. Khoshnevisan, Sukanto Bhattacharya, Florentin Smarandache

**Comments:** 87 pages

The purpose of this book is to apply the Artificial Intelligence and control systems to
different real models.

**Category:** Artificial Intelligence

[3] **viXra:1003.0064 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** M. C. Florea, J. Dezert, P. Valin, Florentin Smarandache, Anne-Laure Jousselme

**Comments:** 8 pages

This paper presents two new promising combination
rules for the fusion of uncertain and potentially highly
conflicting sources of evidences in the theory of belief functions
established first in Dempster-Shafer Theory (DST) and
then recently extended in Dezert-Smarandache Theory
(DSmT). Our work is to provide here new issues to palliate
the well-known limitations of Dempster's rule and to work
beyond its limits of applicability. Since the famous Zadeh's
criticism of Dempster's rule in 1979, many researchers have
proposed new interesting alternative rules of combination to
palliate the weakness of Dempster's rule in order to provide
acceptable results specially in highly conflicting situations.
In this work, we present two new combination rules: the
class of Adaptive Combination Rules (ACR) and a new efficient
Proportional Conflict Redistribution (PCR) rule. Both
rules allow to deal with highly conflicting sources for static
and dynamic fusion applications. We present some interesting
properties for ACR and PCR rules and discuss some
simulation results obtained with both rules for Zadeh's problem
and for a target identification problem.

**Category:** Artificial Intelligence

[2] **viXra:1003.0060 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Xin-De Li, Xian-Zhong Dai, Jean Dezert, Florentin Smarandache

**Comments:** 6 pages

Most of modern systems for information retrieval, fusion
and management have to deal more and more with information
expressed quatitatively (by linguistic labels) since
human reports are better and easier expressed in natural
language than with numbers. In this paper, we propose
to use Herrera-Martínez' 2-Tuple linguistic representation
model (i.e. equidistant linguistic labels with a numeric
value assessment) for reasoning with uncertain and qualitative
information in Dezert-Smarandache Theory (DSmT)
framework to preserve the precision and the efficiency of
the fusion of linguistic information expressing the expert's
qualitative beliefs. We present operators to deal with the
2-Tuples and show from a simple example how qualitative
DSmT-based fusion rules can be used for qualitative reasoning
and fusioning under uncertainty.

**Category:** Artificial Intelligence

[1] **viXra:1003.0059 [pdf]**
*submitted on 6 Mar 2010*

**Authors:** Xin-De Li, Florentin Smarandache, Xian-Zhong Dai

**Comments:** 12 pages

Modern systems for information retrieval, fusion and management need to deal more and more with information
coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this paper, we
propose and use two new 2-Tuple linguistic representation models (i.e., a distribution function model (DFM) and an improved
Herrera-Martínez's model) jointly with the fusion rules developed in Dezert-Smarandache Theory (DSmT), in order to
combine efficiently qualitative information expressed in term of qualitative belief functions. The two models both preserve
the precision and improve the efficiency of the fusion of linguistic information expressing the global expert's opinion. However,
DFM is more general and efficient than the latter, especially for unbalanced linguistic labels. Some simple examples are also
provided to show how the 2-Tuple qualitative fusion rules are performed and their advantages.

**Category:** Artificial Intelligence