# Haut PDF The approach in Markov decision processes revisited

### The approach in Markov decision processes revisited

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### Collision Avoidance for Unmanned Aircraft using Markov Decision Processes

**the**flight dynamics, intruder behavior, and sensor char- acteristics and attempt to optimize

**the**avoidance strategy so that a predefined cost function is ...minimized.

**The**cost function could take ...

23

### Constrained Markov Decision Processes with Total Expected Cost Criteria

**the**optimal value and an optimal stationary policy for ...available

**in**[1] but re- quired

**the**strong assumption that s(β, u) is finite for any ...excludes

**the**shortest path problem ...

3

### A Learning Design Recommendation System Based on Markov Decision Processes

**the**transition ܽ ԡܶܵሺ݄ܶ݁ܽܿ݁ݎሻǡ ܶܵሺݏ ᇱ ሻԡ is a distance factor between

**the**teacher’s teaching styles and

**the**learning object ݏ ᇱ teaching ...between

**the**learning styles of a learner or a ...

9

### DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes

**the**MDP as a single problem, but find more compact [Sanner and McAllester, 2005; Sanner et ...ours

**in**that it de- composes a large MDP based on

**the**connectivity of

**the**...and,

**in**...

9

### Smart Sampling for Lightweight Verification of Markov Decision Processes

**the**authors present learning algorithms to bound

**the**maximum probability of reachability properties of ...MDPs.

**The**algorithms work by refining upper and lower bounds associated to individual ...

14

### Strong Uniform Value in Gambling Houses and Partially Observable Markov Decision Processes

**the**state space and action sets are finite, Blackwell [6] has proved

**the**existence of a pure strategy that is optimal for every discount factor close to 0, and one can deduce that

**the**strong ...

25

### Approximate solution methods for partially observable Markov and semi-Markov decision processes

**In**

**the**last part of this thesis (Chapters 10 and 11) we consider approximation algorithms for finite space POMDPs and MDPs under

**the**reinforcement learning ...from

**the**previous ...

169

### Non-Stationary Markov Decision Processes a Worst-Case Approach using Model-Based Reinforcement Learning

**the**right since MDP 0 does not capture this risk. As a result,

**the**= 0 case reflects a favorable evolution for DP-snapshot and a bad one for ...RATS.

**The**opposite occurs with = 1 where ...

19

### Aggregating Optimistic Planning Trees for Solving Markov Decision Processes

**the**inverted pendulum benchmark problem, showing

**the**sum of discounted rewards for simulations of 50 time ...steps.

**The**algorithms are compared for several budgets.

**In**

**the**cases of ...

9

### Efficient Policies for Stationary Possibilistic Markov Decision Processes

**the**possibility degree of

**the**other one is uniformly fired

**in**...generated.

**The**two algorithms are compared ...Success,

**the**percentage of optimal solutions provided by Bounded value ...

12

### Markov Decision Petri Net and Markov Decision Well-Formed Net Formalisms

**in**our framework, many components may have a similar ...define

**Markov**

**Decision**Well-formed nets (MDWN) similarly as we do for ...MDPNs.

**The**semantics of a model is then easily obtained by ...

20

### Large Markov Decision Processes based management strategy of inland waterways in uncertain context

**the**emission of greenhouse gas (GHG).

**The**last report of IPCC [1] indicate that anthropogenic GHG emissions “came by 11% from transport” from 2000 to ...measures

**in**

**the**transport sector. ...

12

### On the fastest finite Markov processes

**the**paper is as follows.

**The**above results (A) and (B) are proved

**in**

**the**next section via a dynamic programming

**approach**, which also provides an alternative proof of

**the**...

35

### Markov concurrent processes

**The**

**approach**we consider

**in**this paper is based on a treatment of concur- rency

**in**a more structural ...evolves

**in**

**the**usual way, and is thus rendered as a sequence of random ...

21

### Approximate Policy Iteration for Generalized Semi-Markov Decision Processes: an Improved Algorithm

15

### Pilot Allocation and Receive Antenna Selection: A Markov Decision Theoretic Approach

**in**this work consists of a transmitter with a single antenna and a receiver with N antenna ...elements.

**The**receiver has a single RF chain, so it needs to decide on

**the**antenna with which it ...

7

### Decentralized Control of Partially Observable Markov Decision Processes Using Belief Space Macro-Actions

**Markov**

**Decision**

**Processes**using Belief Space Macro-actions Shayegan Omidshafiei, Ali-akbar Agha-mohammadi, Christopher Amato, Jonathan ...Abstract—

**The**focus of this paper is on ...

9

### Strong Uniform Value in Gambling Houses and Partially Observable Markov Decision Processes

**the**state space and action sets are finite, Blackwell [6] has proved

**the**existence of a pure strategy that is optimal for every discount factor close to 0, and one can deduce that

**the**strong ...

26

### Pathwise uniform value in gambling houses and Partially Observable Markov Decision Processes

**the**

**decision**-maker may not be perfectly informed of

**the**current state ...if

**the**state variable represents a resource stock (like

**the**amount of oil

**in**an oil field), ...

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