158 resultados para Learning-Content-System

em Indian Institute of Science - Bangalore - Índia


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Learning automata arranged in a two-level hierarchy are considered. The automata operate in a stationary random environment and update their action probabilities according to the linear-reward- -penalty algorithm at each level. Unlike some hierarchical systems previously proposed, no information transfer exists from one level to another, and yet the hierarchy possesses good convergence properties. Using weak-convergence concepts it is shown that for large time and small values of parameters in the algorithm, the evolution of the optimal path probability can be represented by a diffusion whose parameters can be computed explicitly.

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Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

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A learning automaton operating in a random environment updates its action probabilities on the basis of the reactions of the environment, so that asymptotically it chooses the optimal action. When the number of actions is large the automaton becomes slow because there are too many updatings to be made at each instant. A hierarchical system of such automata with assured c-optimality is suggested to overcome that problem.The learning algorithm for the hierarchical system turns out to be a simple modification of the absolutely expedient algorithm known in the literature. The parameters of the algorithm at each level in the hierarchy depend only on the parameters and the action probabilities of the previous level. It follows that to minimize the number of updatings per cycle each automaton in the hierarchy need have only two or three actions.

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A new clustering technique, based on the concept of immediato neighbourhood, with a novel capability to self-learn the number of clusters expected in the unsupervized environment, has been developed. The method compares favourably with other clustering schemes based on distance measures, both in terms of conceptual innovations and computational economy. Test implementation of the scheme using C-l flight line training sample data in a simulated unsupervized mode has brought out the efficacy of the technique. The technique can easily be implemented as a front end to established pattern classification systems with supervized learning capabilities to derive unified learning systems capable of operating in both supervized and unsupervized environments. This makes the technique an attractive proposition in the context of remotely sensed earth resources data analysis wherein it is essential to have such a unified learning system capability.

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A quantitative structural investigation was carried out on (1-y)PbZrxTi1-xO3-yPbZn(1/3)Nb(2/3)O(3) where y=0.1 and 0.2 ((1-y)PZT-yPZN). High resolution XRD data have been used for quantitative phase analysis. The nominal compositions were prepared by a two-step low temperature calcining solid-state method. The sintered samples show an average grain size of 1-2 mu m. It is demonstrated that the increase in the concentration of PZN leads to the shift of the morphotropic phase boundary (MPB) of PZT towards the PbZrO3 end member. In the present work, an effort has been made to quantitatively determine the MPB phase contents and to regain the coexistence of tetragonal and monoclinic phases by varying the value of x(i.e. Zr/Ti ratio). The width of the MPB becomes considerably larger for y=0.10 and 0.20 as compared to pure PZT. This is attributed to the considerably lower grain size of our samples resulting from the adopted preparation method. (C) 2010 Elsevier B.V. All rights reserved.

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In many problems of decision making under uncertainty the system has to acquire knowledge of its environment and learn the optimal decision through its experience. Such problems may also involve the system having to arrive at the globally optimal decision, when at each instant only a subset of the entire set of possible alternatives is available. These problems can be successfully modelled and analysed by learning automata. In this paper an estimator learning algorithm, which maintains estimates of the reward characteristics of the random environment, is presented for an automaton with changing number of actions. A learning automaton using the new scheme is shown to be e-optimal. The simulation results demonstrate the fast convergence properties of the new algorithm. The results of this study can be extended to the design of other types of estimator algorithms with good convergence properties.

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This paper analyses the behaviour of a general class of learning automata algorithms for feedforward connectionist systems in an associative reinforcement learning environment. The type of connectionist system considered is also fairly general. The associative reinforcement learning task is first posed as a constrained maximization problem. The algorithm is approximated hy an ordinary differential equation using weak convergence techniques. The equilibrium points of the ordinary differential equation are then compared with the solutions to the constrained maximization problem to show that the algorithm does behave as desired.

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A strong influence of Ni content on the diffusion-controlled growth of the (Cu,Ni)(3)Sn and (Cu,Ni)(6)Sn-5 phases by coupling different Cu(Ni) alloys with Sn in the solid state is reported. The continuous increase in the thickness ratio of (Cu,Ni)(6)Sn-5 to (Cu,Ni)(3)Sn with the Ni content is explained by combined kinetic and thermodynamic arguments as follows: (i) The integrated interdiffusion coefficient does not change for the (Cu,Ni)(3)Sn phase up to 2.5 at.% Ni and decreases drastically for 5 at.% Ni. On the other hand, there is a continuous increase in the integrated interdiffusion coefficient for (Cu,Ni)(6)Sn-5 as a function of increasing Ni content. (ii) With the increase in Ni content, driving forces for the diffusion of components increase for both components in both phases but at different rates. However, the magnitude of these changes alone is not large enough to explain the high difference in the observed growth rate of the product phases because of Ni addition. (iv) Kirkendall marker experiments indicate that the Cu6Sn5 phase grows by diffusion of both Cu and Sn in the binary case. However, when Ni is added, the growth is by diffusion of Sn only. (v) Also, the observed grain refinement in the Cu6Sn5 phase with the addition of Ni suggests that the grain boundary diffusion of Sn may have an important role in the observed changes in the growth rate.

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A new quaternary fast-ion conducting silver molybdo-arsenate [Agl-Ag2O-(MoO3 + As2O5)] (SMA) glassy system has been prepared using the melt-quenching technique for various dopant salt (Agl) concentrations by fixing the formers (MoO3 + As2O5) composition and the modifier (Ag2O) to formers (M/F) ratio. The prepared compounds were characterized by X-ray diffraction. The impedance measurements were made on different Agl compositions of the SMA glasses as a function of frequency (6.5 Hz-65 kHz) and temperature (303-343 K), using the Solatron frequency-response analyser(model 1250). The bulk conductivity and the appropriate physical model (equivalent circuit) of the SMA glass were obtained from the impedance analysis. The a.c. conductivity was calculated for different Agl compositions of SMA glasses at various temperatures and the obtained a.c. conductivity results were analysed using Jonscher's Universal Law. The conduction mechanism for the highest conducting SMA glassy compound has been explained using the diffusion path model.

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The floating-zone method with different growth ambiences has been used to selectively obtain hexagonal or orthorhombic DyMnO3 single crystals. The crystals were characterized by x-ray powder diffraction of ground specimens and a structure refinement as well as electron diffraction. We report magnetic susceptibility, magnetization and specific heat studies of this multiferroic compound in both the hexagonal and the orthorhombic structure. The hexagonal DyMnO3 shows magnetic ordering of Mn3+ (S = 2) spins on a triangular Mn lattice at T-N(Mn) = 57 K characterized by a cusp in the specific heat. This transition is not apparent in the magnetic susceptibility due to the frustration on the Mn triangular lattice and the dominating paramagnetic susceptibility of the Dy3+ (S = 9/2) spins. At T-N(Dy) = 3 K, a partial antiferromagnetic order of Dy moments has been observed. In comparison, the magnetic data for orthorhombic DyMnO3 display three transitions. The data broadly agree with results from earlier neutron diffraction experiments, which allows for the following assignment: a transition from an incommensurate antiferromagnetic ordering of Mn3+ spins at T-N(Mn) = 39 K, a lock-in transition at Tlock-in = 16 K and a second antiferromagnetic transition at T-N(Dy) = 5 K due to the ordering of Dy moments. Both the hexagonal and the orthorhombic crystals show magnetic anisotropy and complex magnetic properties due to 4f-4f and 4f-3d couplings.

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Recent research in modelling uncertainty in water resource systems has highlighted the use of fuzzy logic-based approaches. A number of research contributions exist in the literature that deal with uncertainty in water resource systems including fuzziness, subjectivity, imprecision and lack of adequate data. This chapter presents a broad overview of the fuzzy logic-based approaches adopted in addressing uncertainty in water resource systems modelling. Applications of fuzzy rule-based systems and fuzzy optimisation are then discussed. Perspectives on the scope for further research are presented.

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Indian society is an agglomeration of several thousand endogamous groups or castes each with a restricted geographical range and a hereditarily determine mode of subsistence. These reproductively isolated castes may be compared to biological species, and the society thought of as a biological community with each caste having its specific ecological niche. In this paper we examine the ecological-niche relationships of castes which are directly dependent on natural resources. Evidence is presented to show that castes living together in the same region had so organized their pattern of resource use as to avoid excessive intercaste competition for limiting resources. Furthermore, territorial division of the total range of the caste regulated intra-caste competition. Hence, a particular plant or animal resource in a given locality was used almost exclusively by a given lineage within a caste generation after generation. This favoured the cultural evolution of traditions ensuring sustainable use of natural resources. This must have contributed significantly to the stability of Indian caste society over several thousand years. The collapse of the base of natural resources and increasing monetarization of the economy has, however, destroyed the earlier complementarity between the different castes and led to increasing conflicts between them in recent years.

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1H NMR spin-lattice relaxation time (T1) studies have been carried out in the temperature range 100 K to 4 K, at two Larmor frequencies 11.4 and 23.3 MHz, in the mixed system of betaine phosphate and glycine phosphite (BPxGPI(1-x)), to study the effects of disorder on the proton group dynamics. Analysis of T1 data indicates the presence of a number of inequivalent methyl groups and a gradual transition from classical reorientations to quantum tunneling rotations. At lower temperatures, microstructural disorder in the local environments of the methyl groups, result in a distribution in the activation energy (Ea) and the torsional energy gap (E01). For certain values of x, the magnetisation recovery shows biexponential behaviour at lower temperatures.

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The anharmonic oscillator under combined sinusoidal and white noise excitation is studied using the Gaussian closure approximation. The mean response and the steady-state variance of the system is obtained by the WKBJ approximation and also by the Fokker Planck equation. The multiple steadystate solutions are obtained and their stability analysis is presented. Numerical results are obtained for a particular set of system parameters. The theoretical results are compared with a digital simulation study to bring out the usefulness of the present approximate theory.