Artificial Intelligence

1207 Submissions

[6] viXra:1207.0062 [pdf] submitted on 2012-07-16 23:17:12

Generalization of the Dependent Function in Extenics for Nested Sets with Common Endpoints to 2D-Space, 3D-Space, and Generally to N-D-Space

Authors: Florentin Smarandache
Comments: 8 Pages.

In this paper we extend Prof. Yang Chunyan and Prof. Cai Wen’s dependent function of a point P with respect to two nested sets X0 X, for the case the sets X0 and X have common ending points, from 1D-space to n-D-space. We give several examples in 2D- and 3D-spaces. When computing the dependent function value k(.) of the optimal point O, we take its maximum possible value. Formulas for computing k(O), and the geometrical determination the Critical Zone are also given.
Category: Artificial Intelligence

[5] viXra:1207.0058 [pdf] submitted on 2012-07-16 05:14:14

Neutrosophic Masses & Indeterminate Models. Applications to Information Fusion

Authors: Florentin Smarandache
Comments: 7 Pages.

In this paper we introduce the indeterminate models in information fusion, which are due either to the existence of some indeterminate elements in the fusion space or to some indeterminate masses. The best approach for dealing with such models is the neutrosophic logic.
Category: Artificial Intelligence

[4] viXra:1207.0057 [pdf] submitted on 2012-07-16 05:15:50

Extended PCR Rules for Dynamic Frames

Authors: Florentin Smarandache, Jean Dezert
Comments: 8 Pages.

In most of classical fusion problems modeled from belief functions, the frame of discernment is considered as static. This means that the set of elements in the frame and the underlying integrity constraints of the frame are fixed forever and they do not change with time. In some applications, like in target tracking for example, the use of such invariant frame is not very appropriate because it can truly change with time. So it is necessary to adapt the Proportional Conflict Redistribution fusion rules (PCR5 and PCR6) for working with dynamical frames. In this paper, we propose an extension of PCR5 and PCR6 rules for working in a frame having some non-existential integrity constraints. Such constraints on the frame can arise in tracking applications by the destruction of targets for example. We show through very simple examples how these new rules can be used for the belief revision process.
Category: Artificial Intelligence

[3] viXra:1207.0056 [pdf] submitted on 2012-07-16 05:17:47

Comparative Study of Contradiction Measures in the Theory of Belief Functions

Authors: Florentin Smarandache, Deqiang Han, Arnaud Martin
Comments: 7 Pages.

Uncertainty measures in the theory of belief functions are important for the uncertainty representation and reasoning. Many measures of uncertainty in the theory of belief functions have been introduced. The degree of discord (or conflict) inside a body of evidence is an important index for measuring uncertainty degree. Recently, distance of evidence is used to define a contradiction measure for quantifying the degree of discord inside a body of evidence. The contradiction measure is actually the weighted summation of the distance values between a given basic belief assignment (bba) and the categorical bba’s defined on each focal element of the given bba redefined in this paper. It has normalized value and can well characterize the self-discord incorporated in bodies of evidence. We propose here, some numerical examples with comparisons among different uncertainty measures are provided, together with related analyses, to show the rationality of the proposed contradiction measure.
Category: Artificial Intelligence

[2] viXra:1207.0040 [pdf] submitted on 2012-07-11 05:41:10

P Vs. NP Solved

Authors: Gurpinder Singh
Comments: 1 Page. this is only existing proof of this problem

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Category: Artificial Intelligence

[1] viXra:1207.0026 [pdf] submitted on 2012-07-06 10:56:56

Consensus Seeking on Moving Neighborhood Model of Random Sector Graphs

Authors: Mitra Ganguly, Timothy Eller
Comments: 5 Pages. technical report in NUI, #551

In this paper, we address consensus seeking problem of dynamical agents on random sector graphs. Random sector graphs are directed geometric graphs and have been investigated extensively. Each agent randomly walks on these graphs and communicates with each other if and only if they coincide on a node at the same time. Extensive simulations are performed to show that global consensus can be reached.
Category: Artificial Intelligence