Cascade Markov Decision Processes: Theory and Applications
نویسنده
چکیده
This paper considers the optimal control of time varying continuous time Markov chains whose transition rates are themselves Markov processes. In one set of problems the solution of an ordinary differential equation is shown to determine the optimal performance and feedback controls, while some other cases are shown to lead to singular optimal control problems which are more difficult to solve. Solution techniques are demonstrated using examples from finance to behavioral decision making.
منابع مشابه
Accelerated decomposition techniques for large discounted Markov decision processes
Many hierarchical techniques to solve large Markov decision processes (MDPs) are based on the partition of the state space into strongly connected components (SCCs) that can be classified into some levels. In each level, smaller problems named restricted MDPs are solved, and then these partial solutions are combined to obtain the global solution. In this paper, we first propose a novel algorith...
متن کاملExistence of Optimal Policies for Semi-Markov Decision Processes Using Duality for Infinite Linear Programming
Semi-Markov decision processes on Borel spaces with deterministic kernels have many practical applications, particularly in inventory theory. Most of the results from general semi-Markov decision processes do not carry over to a deterministic kernel since such a kernel does not provide “smoothness.” We develop infinite dimensional linear programming theory for a general stochastic semi-Markov d...
متن کاملMethods and Applications of (MAX, +) Linear Algebra
Exotic semirings such as the “(max;+) semiring” (R[f 1g;max;+), or the “tropical semiring” (N[f+1g;min;+), have been invented and reinvented many times since the late fifties, in relation with various fields: performance evaluation of manufacturing systems and discrete event system theory; graph theory (path algebra) and Markov decision processes, Hamilton-Jacobi theory; asymptotic analysis (lo...
متن کاملStochastic processes in survival analysis
The objects studied in survival and event history analysis are stochastic phenomena developing over time. It is therefore natural to use the highly developed theory of stochastic processes. We argue that this theory should be used more in event history analysis. Some specific examples are treated: Markov chains, martingale-based counting processes, birth type processes, diffusion processes and ...
متن کاملMarkov Decision Processes
The theory of Markov Decision Processes is the theory of controlled Markov chains. Its origins can be traced back to R. Bellman and L. Shapley in the 1950’s. During the decades of the last century this theory has grown dramatically. It has found applications in various areas like e.g. computer science, engineering, operations research, biology and economics. In this article we give a short intr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- CoRR
دوره abs/1509.00392 شماره
صفحات -
تاریخ انتشار 2015