Exact controllability for a nonlinear stochastic wave equation.
Existence of average optimal policies in Markov control processes with strictly unbounded costs
Existence of optimal nonanticipating controls in piecewise deterministic control problems
Optimal nonanticipating controls are shown to exist in nonautonomous piecewise deterministic control problems with hard terminal restrictions. The assumptions needed are completely analogous to those needed to obtain optimal controls in deterministic control problems. The proof is based on well-known results on existence of deterministic optimal controls.
Explicit formulae of distributions and densities of characteristics of a dynamic advertising and pricing model
We analyze the optimal sales process of a stochastic advertising and pricing model with constant demand elasticities. We derive explicit formulae of the densities of the (optimal) sales times and (optimal) prices when a fixed finite number of units of a product are to be sold during a finite sales period or an infinite one. Furthermore, for any time t the exact distribution of the inventory, i.e. the number of unsold items, at t is determined and will be expressed in terms of elementary functions....
Exponential convergence for a convexifying equation
We consider an evolution equation similar to that introduced by Vese in [Comm. Partial Diff. Eq. 24 (1999) 1573–1591] and whose solution converges in large time to the convex envelope of the initial datum. We give a stochastic control representation for the solution from which we deduce, under quite general assumptions that the convergence in the Lipschitz norm is in fact exponential in time.
Exponential convergence for a convexifying equation
We consider an evolution equation similar to that introduced by Vese in [Comm. Partial Diff. Eq. 24 (1999) 1573–1591] and whose solution converges in large time to the convex envelope of the initial datum. We give a stochastic control representation for the solution from which we deduce, under quite general assumptions that the convergence in the Lipschitz norm is in fact exponential in time.
Exponential convergence for a convexifying equation
We consider an evolution equation similar to that introduced by Vese in [Comm. Partial Diff. Eq. 24 (1999) 1573–1591] and whose solution converges in large time to the convex envelope of the initial datum. We give a stochastic control representation for the solution from which we deduce, under quite general assumptions that the convergence in the Lipschitz norm is in fact exponential in time.
Exponential utility optimization, indifference pricing and hedging for a payment process
We deal with pricing and hedging for a payment process. We investigate a Black-Scholes financial market with stochastic coefficients and a stream of liabilities with claims occurring at random times, continuously over the duration of the contract and at the terminal time. The random times of the claims are generated by a random measure with a stochastic intensity of jumps. The claims are written on the asset traded in the financial market and on the non-tradeable source of risk driven by the random...
Finite utility on financial markets with asymmetric information and structure properties of the price dynamics
Finite-dimensionality of information states in optimal control of stochastic systems: a Lie algebraic approach
In this paper we introduce the sufficient statistic algebra which is responsible for propagating the sufficient statistic, or information state, in the optimal control of stochastic systems. Certain Lie algebraic methods widely used in nonlinear control theory, are then employed to derive finite- dimensional controllers. The sufficient statistic algebra enables us to determine a priori whether there exist finite-dimensional controllers; it also enables us to classify all finite-dimensional controllers....
Forecast horizon in dynamic family of one-dimensional control problems [Book]
Full cooperation applied to environmental improvements
We analyse the case of certificates of environmental improvements and full cooperation of two identical agents. We model pollution levels as geometric Brownian motions with quadratic costs of improvements. Our main result is the construction of the optimal improvements strategy in the case of separate actions, collusive actions and fusion. In certain range of the model parameters, the fusion solution generates lower pollution levels than separate and collusive actions.
Geometry of non-holonomic diffusion
We study stochastically perturbed non-holonomic systems from a geometric point of view. In this setting, it turns out that the probabilistic properties of the perturbed system are intimately linked to the geometry of the constraint distribution. For -Chaplygin systems, this yields a stochastic criterion for the existence of a smooth preserved measure. As an application of our results we consider the motion planning problem for the noisy two-wheeled robot and the noisy snakeboard.
Growth rates and average optimality in risk-sensitive Markov decision chains
In this note we focus attention on characterizations of policies maximizing growth rate of expected utility, along with average of the associated certainty equivalent, in risk-sensitive Markov decision chains with finite state and action spaces. In contrast to the existing literature the problem is handled by methods of stochastic dynamic programming on condition that the transition probabilities are replaced by general nonnegative matrices. Using the block-triangular decomposition of a collection...
Hard and soft sub-time-optimal controllers for a mechanical system with uncertain mass
Hypercontractivity of solutions to Hamilton-Jacobi equations
We show that solutions to some Hamilton-Jacobi Equations associated to the problem of optimal control of stochastic semilinear equations enjoy the hypercontractivity property.
Identification of optimal policies in Markov decision processes
In this note we focus attention on identifying optimal policies and on elimination suboptimal policies minimizing optimality criteria in discrete-time Markov decision processes with finite state space and compact action set. We present unified approach to value iteration algorithms that enables to generate lower and upper bounds on optimal values, as well as on the current policy. Using the modified value iterations it is possible to eliminate suboptimal actions and to identify an optimal policy...
Infinite-horizon Markov control processes with undiscounted cost criteria: from average to overtaking optimality
We consider discrete-time Markov control processes on Borel spaces and infinite-horizon undiscounted cost criteria which are sensitive to the growth rate of finite-horizon costs. These criteria include, at one extreme, the grossly underselective average cost
Information pricing for portfolio optimization
Interactive approach based on stochastic dominance