# Markov decision process

## Papers overview

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Review

2017

Review

2017

- ArXiv
- 2017

Reinforcement learning is considered to be a strong AI paradigm which can be used to teach machines through interaction with theâ€¦Â (More)

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2012

Highly Cited

2012

- ICML
- 2012

We explain the need for safe exploration methods in Markov Decision Processes and present three different formulations of safetyâ€¦Â (More)

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2005

Highly Cited

2005

- Operations Research
- 2005

Optimal solutions to Markov decision problems may be very sensitive with respect to the state transition probabilities. In manyâ€¦Â (More)

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2003

Highly Cited

2003

- AAMAS
- 2003

There has been substantial progress with formal models for sequential decision making by individual agents using the Markovâ€¦Â (More)

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2000

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2000

- 2000

The theory of Markov Decision Processes is the theory of controlled Markov chains. Its origins can be traced back to R. Bellmanâ€¦Â (More)

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2000

Highly Cited

2000

- 2000

The bidding decision making problem is studied from a supplierâ€™s viewpoint in a spot market environment. The decision-makingâ€¦Â (More)

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1999

Highly Cited

1999

- Machine Learning
- 1999

A critical issue for the application of Markov decision processes (MDPs) to realistic problems is how the complexity of planningâ€¦Â (More)

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1998

Highly Cited

1998

- ICASSP
- 1998

In this paper we introduce a stochastic model for dialogue systems based on Markov decision process. Within this framework weâ€¦Â (More)

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1998

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1998

- 1998

This dissertation investigates the use of hierarchy and problem decomposition as a means of solving large, stochastic, sequentialâ€¦Â (More)

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1997

Highly Cited

1997

- AAAI/IAAI
- 1997

We use the notion of stochastic bisimulation homo-geneity to analyze planning problems represented as Markov decision processesâ€¦Â (More)

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