Free boundary value problems and hjb equations for the stochastic optimal control of elasto-plastic oscillators

We consider the optimal stopping and optimal control problems related to stochastic variational inequalities modeling elasto-plastic oscillators subject to random forcing. We formally derive the corresponding free boundary value problems and Hamilton-Jacobi-Bellman equations which belong to a class of nonlinear partial of differential equations with nonlocal Dirichlet boundary conditions. Then, we focus on solving numerically these equations by employing a combination of Howard’s algorithm and the numerical approach [A backward Kolmogorov equation approach to compute means, moments and correlations of non-smooth stochastic dynamical systems; Mertz, Stadler, Wylie; 2017] for this type of boundary conditions. Numerical experiments are given

Free boundary value problems and hjb equations for the stochastic optimal control of elasto-plastic oscillators

We consider the optimal stopping and optimal control problems related to stochastic variational inequalities modeling elasto-plastic oscillators subject to random forcing. We formally derive the corresponding free boundary value problems and Hamilton-Jacobi-Bellman equations which belong to a class of nonlinear partial of differential equations with nonlocal Dirichlet boundary conditions. Then, we focus on solving numerically these equations by employing a combination of Howard’s algorithm and the numerical approach [A backward Kolmogorov equation approach to compute means, moments and correlations of non-smooth stochastic dynamical systems; Mertz, Stadler, Wylie; 2017] for this type of boundary conditions. Numerical experiments are given

Transforming and refining abstract constraint specifications

Abstract. To use constraint technology to solve a problem, the solutions to the problem must first be characterised, or modelled, by a set of constraints that they must satisfy. A significant part of the modelling process can be characterised as refinement, the process of generating a concrete model from an abstract specification of the problem. Expert modellers also identify and perform transformations that can dramatically reduce the effort needed to solve the problem by systematic search. Through a case study of modelling a simplified version of the SONET fibre-optic communication problem, this paper examines the processes of refinement and transformation, and especially the interaction between the two.

Problem representation for refinement

In this paper we attempt to develop a problem representation technique which enables the decomposition of a problem into subproblems such that their solution in sequence constitutes a strategy for solving the problem. An important issue here is that the subproblems generated should be easier than the main problem. We propose to represent a set of problem states by a statement which is true for all the members of the set. A statement itself is just a set of atomic statements which are binary predicates on state variables. Then, the statement representing the set of goal states can be partitioned into its subsets each of which becomes a subgoal of the resulting strategy. The techniques involved in partitioning a goal into its subgoals are presented with examples