Computation of S-adapted Equilibria in Piecewise Deterministic Games via Stochastic Programming Methods
نویسندگان
چکیده
This paper explores a class of equilibria for piecewise deterministic differential games, with an information structure permitting the players to adapt to the jump Markov disturbance sample path but not to the continuous state trajectory. This information structure is therefore halfway between the open-loop and feedback ones. The paper shows that these equi-libria can be approximated through a sequence of stochastic programming-variational inequalities problems for which eecient computational techniques exist.
منابع مشابه
Multi-choice stochastic bi-level programming problem in cooperative nature via fuzzy programming approach
In this paper, a Multi-Choice Stochastic Bi-Level Programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general tran...
متن کاملStationary equilibria in stochastic games: structure, selection, and computation
This paper is the rst to introduce an algorithm to compute stationary equilibria in stochastic games, and shows convergence of the algorithm for almost all such games. Moreover, since in general the number of stationary equilibria is overwhelming, we pay attention to the issue of equilibrium selection. We do this by extending the linear tracing procedure to the class of stochastic games, called...
متن کاملStochastic Congestion Management Considering Power System Uncertainties
Congestion management in electricity markets is traditionally done using deterministic values of power system parameters considering a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties. The uncertainty sources that are modeled in the proposed stochastic framework consist of contingencie...
متن کاملEffects of Probability Function on the Performance of Stochastic Programming
Stochastic programming is a valuable optimization tool where used when some or all of the design parameters of an optimization problem are defined by stochastic variables rather than by deterministic quantities. Depending on the nature of equations involved in the problem, a stochastic optimization problem is called a stochastic linear or nonlinear programming problem. In this paper,a stochasti...
متن کاملDecision making in forest management with consideration of stochastic prices
The optimal harvesting policy is calculated as a function of the entering stock, the price state, the harvesting cost, and the rate of interest in the capital market. In order to determine the optimal harvest schedule, the growth function and stumpage price process are estimated for the Swedish mixed species forests. The stumpage price is assumed to follow a stochastic Markov process. A stoch...
متن کامل