Add to ORKGThe self-tuning method of adaptive control for diffusions consists of estimating the unknown parameter on line and using its current estimate as the true parameter for the selection of the control at each time. The a.s. optimality of this scheme for the ergodic or long-run average criterion can be established under an identifiabitity condition on the system, but may fail otherwise. We present a modified self-tuning scheme along the lines of the Kumar-Becker-Lin scheme for Markov chains and prove its a.s. optimality. Several heuristic issues related to this scheme are also discussed
100 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.In this thesis we consider th...
Abstract. Three distinct controlled ergodic Markov models are considered here. The models are a disc...
Consider a countable state controlled Markov chain whose transition probability is specified up to a...
The self-tuning method of adaptive control for diffusions consists of estimating the unknown paramet...
The self-tuning method of adaptive control for diffusions consists of estimating the unknown paramet...
The self-tuning approach to adaptive control is applied to a class of Markov chains called nearest-n...
This paper considers Bayesian parameter estimation and an associated adaptive control scheme for con...
A control problem for a partially observable Markov chain depending on a parameter with long run ave...
We consider an adaptive finite state controlled Markov chain with partial state information, motivat...
Abstract. This paper considers Bayesian parameter estimation and an associated adaptive control sche...
A recursive self-tuning control scheme for finite Markov chains is proposed wherein the unknown para...
This is the published version, also available here: http://dx.doi.org/10.1137/S0363012996298369.Thre...
For self-tuning control of a finite state Markov chain whose parametrized transition probabilities s...
The explicit self-tuning control of linear systems with constant but unknown parameters is analysed....
The optimal steady-state control, and suboptimal adaptive control, of disturbed single-input-output ...
100 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.In this thesis we consider th...
Abstract. Three distinct controlled ergodic Markov models are considered here. The models are a disc...
Consider a countable state controlled Markov chain whose transition probability is specified up to a...
The self-tuning method of adaptive control for diffusions consists of estimating the unknown paramet...
The self-tuning method of adaptive control for diffusions consists of estimating the unknown paramet...
The self-tuning approach to adaptive control is applied to a class of Markov chains called nearest-n...
This paper considers Bayesian parameter estimation and an associated adaptive control scheme for con...
A control problem for a partially observable Markov chain depending on a parameter with long run ave...
We consider an adaptive finite state controlled Markov chain with partial state information, motivat...
Abstract. This paper considers Bayesian parameter estimation and an associated adaptive control sche...
A recursive self-tuning control scheme for finite Markov chains is proposed wherein the unknown para...
This is the published version, also available here: http://dx.doi.org/10.1137/S0363012996298369.Thre...
For self-tuning control of a finite state Markov chain whose parametrized transition probabilities s...
The explicit self-tuning control of linear systems with constant but unknown parameters is analysed....
The optimal steady-state control, and suboptimal adaptive control, of disturbed single-input-output ...
100 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1985.In this thesis we consider th...
Abstract. Three distinct controlled ergodic Markov models are considered here. The models are a disc...
Consider a countable state controlled Markov chain whose transition probability is specified up to a...