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
... of 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 ...
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Constrained Markov Decision Processes with Total Expected Cost Criteria
... pute 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 ...
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A Learning Design Recommendation System Based on Markov Decision Processes
... after 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 ...
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DetH*: Approximate Hierarchical Solution of Large Markov Decision Processes
... treat 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 ...
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Smart Sampling for Lightweight Verification of Markov Decision Processes
... [6] 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 ...
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Strong Uniform Value in Gambling Houses and Partially Observable Markov Decision Processes
... When 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 ...
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Approximate solution methods for partially observable Markov and semi-Markov decision processes
... Algorithms 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 ...
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Non-Stationary Markov Decision Processes a Worst-Case Approach using Model-Based Reinforcement Learning
... to 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 ...
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Aggregating Optimistic Planning Trees for Solving Markov Decision Processes
... on 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 ...
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Efficient Policies for Stationary Possibilistic Markov Decision Processes
... and 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 ...
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Markov Decision Petri Net and Markov Decision Well-Formed Net Formalisms
... i.e, 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 ...
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Large Markov Decision Processes based management strategy of inland waterways in uncertain context
... to 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. ...
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On the fastest finite Markov processes
... of 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 ...
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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 ...
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Approximate Policy Iteration for Generalized Semi-Markov Decision Processes: an Improved Algorithm
... To summarize, the improvement of the current policy is performed online: for each visited state starting in s0 we perform one Bellman backup using the value function evaluation from the[r] ...
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Pilot Allocation and Receive Antenna Selection: A Markov Decision Theoretic Approach
... model 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 ...
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Decentralized Control of Partially Observable Markov Decision Processes Using Belief Space Macro-Actions
... Observable 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 ...
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Strong Uniform Value in Gambling Houses and Partially Observable Markov Decision Processes
... When 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 ...
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Pathwise uniform value in gambling houses and Partially Observable Markov Decision Processes
... situations, 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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