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Stochastic Optimization: Proceedings of the International Conference, Kiev, 1984: Lecture Notes in Control and Information Sciences, cartea 81

Editat de Vadim I. Arkin, A. Shiraev, R. Wets
en Limba Engleză Paperback – iun 1986

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Specificații

ISBN-13: 9783540166597
ISBN-10: 3540166599
Pagini: 772
Ilustrații: X, 759 p. 5 illus.
Dimensiuni: 170 x 244 x 41 mm
Greutate: 1.21 kg
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seria Lecture Notes in Control and Information Sciences

Locul publicării:Berlin, Heidelberg, Germany

Public țintă

Research

Cuprins

A martingale approach to partially observable controlled stochastic systems.- On the limiting distribution of extremum points for certain stochastic optimization models.- The structure of persistently nearly-optimal strategies in stochastic dynamic programming problems.- On the derivation of a filtering equation for a non-observable semimartingale.- On the representation of functionals of a wiener sheet by stochastic integrals.- The maximum principle for optimal control of diffusions with partial information.- Explicit solution of a consumption/investment problem.- On the asymptotic behavior of some optimal estimates of parameters of nonlinear regression functions.- On the ?-optimal control of a stochastic integral equation with an unknown parameter.- Some properties of value functions for controlled diffusion processes.- Stochastic control with state constraints and non-linear elliptic equations with infinite boundary conditions.- On the weak convergence of controlled semi-martingales.- Estimation of parameters and control of systems with unknown parameters.- On recursive approximations with error bounds in nonlinear filtering.- On approximations to discrete-time stochastic control problems.- On lexicographical optimality criteria in controlled markov chains.- Canonical correlations, hankel operatiors and markovian representations of multivariate stationary Gaussian processes.- The maximum principle in stochastic problems with non-fixed random control time.- Optimal control of stochastic integral equations.- Some direct methods for computing optimal estimators for forecasting and filtering problems involving stochastic processes.- On functional equations of discrete dynamic programming.- Risk-sensitive and Hamiltonian formulations in optimal control.- Martingales insurvival analysis.- Markov decision processes with both continuous and impulsive control.- Stochastic programming methods: Convergence and non-asymptotic estimation of the convergence rate.- Solution of a stochastic programming problem concerning the distribution of water resources.- Limit theorems for processes generated by stochastic optimization algorithms.- On the structure of optimality criteria in stochastic optimization models.- Strong laws for a class of path-dependent stochastic processes with applications.- The generalized extremum in the class of discontinuous functions and finitely additive integration.- Convex multivalued mappings and stochastic models of the dynamics of economic systems.- Stability in stochastic programming — Probabilistic constraints.- Duality in improper mathematical programming problems under uncertainty.- Equilibrium states of monotonic operators and equilibrium trajectories in stochastic economic models.- Finite horizon approximates of infinite horizon stochastic programs.- Stochastic optimization techniques for finding optimal submeasures.- Strong consistency theorems related to stochastic quasi-Newton methods.- Stochastic gradient methods for optimizing electrical transportation networks.- On the functional dependence between the available information and the chosen optimality principle.- Uncertainty in stochastic programming.- Stochastic programming models for safety stock allocation.- Direct averaging and perturbed test function methods for weak convergence.- On the approximation of stochastic convex programming problems.- Extremal problems with probability measures, functionally closed preorders and strong stochastic dominance.- Expected value versus probability of ruin strategies.- Controlled random search procedures forglobal optimization.- On Bayesian methods in nondifferential and stochastic programming.- On stochastic programming in hilbert space.- Reduction of risk using a differentiated approach.- A stochastic lake eutrophication management model.- A dynamic model of market behavior.- Recursive stochastic gradient procedures in the presence of dependent noise.- Random search as a method for optimization and adaptation.- Linear-quadratic programming problems with stochastic penalties: The finite generation algorithm.- Convergence of stochastic infima: Equi-semicontinuity.- Growth rates and optimal paths in stochastic models of expanding economies.- Extremum problems depending on a random parameter.- Adaptive control of parameters in gradient algorithms for stochastic optimization.- Stochastic models and methods of optimal planning.- Differential inclusions and controlled systems: Properties of solutions.- Guaranteed estimation of reachable sets for controlled systems.- Methods of group pursuit.- An averaging principle for optimal control problems with singular perturbations.- On a certain class of inverse problems in control system dynamics.- Simultaneous estimation of states and parameters in control systems with incomplete data.- Approximate solutions of differential games using mixed strategies.- On the solution sets for uncertain systems with phase constraints.- Existence of a value for a general zero-sum mixt game.- Positional modeling of stochastic control in dynamical systems.- Use of the h-convex set method in differential games.- A linear differential pursuit game.- Methods of constructing guaranteed estimates of parameters of linear systems and their statistical properties.- Stochastic and deterministic control: Differential inequalities.- The search for singular extremals.- On the smoothness of the bellman function in optimal control problems with incomplete data.