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Infinite horizon average cost dynamic programming subject to ambiguity on conditional distribution
- Source :
- CDC, Proceedings of the IEEE Conference on Decision and Control
- Publication Year :
- 2015
- Publisher :
- IEEE, 2015.
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Abstract
- This paper addresses the optimality of stochastic control strategies based on the infinite horizon average cost criterion, subject to total variation distance ambiguity on the conditional distribution of the controlled process. This stochastic optimal control problem is formulated using minimax theory, in which the minimization is over the control strategies and the maximization is over the conditional distributions. Under the assumption that, for every stationary Markov control law the maximizing conditional distribution of the controlled process is irreducible, we derive a new dynamic programming recursion which minimizes the future ambiguity, and we propose a new policy iteration algorithm. The new dynamic programming recursion includes, in addition to the standard terms, the oscillator semi-norm of the cost-to-go. The maximizing conditional distribution is found via a water-filling algorithm. The implications of our results are demonstrated through an example. © 2015 IEEE. 54rd IEEE Conference on Decision and Control,CDC 2015 7171 7176
- Subjects :
- Optimization
Mathematical optimization
Iterative methods
Conditional distribution
Markov process
Aerospace electronics
Dynamic programming
symbols.namesake
Control theory
Heuristic algorithms
Mathematics
Stochastic control
Optimal controls
Stochastic systems
Infinite horizon average costs
Markov chain
Control strategies
Markov processes
Policy iteration algorithms
Variable-order Markov model
Recursion (computer science)
Optimal control systems
Conditional probability distribution
Optimal control
Stochastic optimal control problem
Costs
Stochastic control systems
symbols
Process control
Markov decision process
Water-filling algorithm
Algorithms
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2015 54th IEEE Conference on Decision and Control (CDC)
- Accession number :
- edsair.doi.dedup.....bfa4ee702aba6ec29bc3449c5298cd3d