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Review

2019

Review

2019

In this paper we discuss policy iteration methods for approximate solution of a finite-state discounted Markov decision problem… Expand

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Review

2017

Review

2017

Online learning is an important property of adaptive dynamic programming (ADP). Online observations contain plentiful dynamics… Expand

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Review

2016

Review

2016

9 5 5 partially observable decision processes 9 5. partially observable total cost markov decision processes. partially observed… Expand

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Highly Cited

2005

Highly Cited

2005

Optimal solutions to Markov decision problems may be very sensitive with respect to the state transition probabilities. In many… Expand

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Highly Cited

2004

Highly Cited

2004

A critical issue for the application of Markov decision processes (MDPs) to realistic problems is how the complexity of planning… Expand

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Highly Cited

2001

Highly Cited

2001

Probabilistic graphical models and decision graphs are powerful modeling tools for reasoning and decision making under… Expand

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Highly Cited

1999

Highly Cited

1999

INTRODUCTION Examples of Constrained Dynamic Control Problems On Solution Approaches for CMDPs with Expected Costs Other Types of… Expand

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Highly Cited

1996

Highly Cited

1996

1 Introduction.- 1.0 Background.- 1.1 Raison d'Etre and Limitations.- 1.2 A Menu of Courses and Prerequisites.- 1.3 For the… Expand

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Highly Cited

1994

Highly Cited

1994

From the Publisher:
The past decade has seen considerable theoretical and applied research on Markov decision processes, as well… Expand

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Highly Cited

1987

Highly Cited

1987

We investigate the complexity of the classical problem of optimal policy computation in Markov decision processes. All three… Expand

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