Stochastic Optimization

Inhaltsverzeichnis

• 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.