Optimisation Techniques with Markov Decision Process
Markov Decision Process Model for Optimisation of Patient Flow
... a Markov decision process (MDP) model over a weekly time horizon to analyse FMC’s bed occupancy patterns with a goal of proposing policies that lead to reduced incidence of ...
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Optimisation of ETL Process Using Partitioning and Parallelization Techniques
... Metadata repository stores execution plans , technical metadata, and business metadata. Business metadata should include dimensionality model and the dependency relationship between dimensional model and data source. ...
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Reachability-based model reduction for Markov decision process
... One example of algorithm for solving SSPs is real-time dynamic programming (RTDP) [4] that, given an SSP and a lower bound for V ∗ , computes an optimal policy for all the relevant states, i.e., all states reachable by ...
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A Markov Decision Process Model for Traffic Prioritisation Provisioning
... the buffer, are not delayed by the lower priority packets. Hence, information of the buffer states is essential in reaching such decisions. Figure 2 illustrates the scenario of packet arrival which re- quires the arbiter ...
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Markov Decision Process modeled with Bandits for Sequential Decision Making in Linear-flow
... sequential decision making process, it is a simpler flow where customers per seeing recommended content on each page can only move forward in the process or drop from ...sequential decision ...
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Techniques for Supporting Prediction of Security Breaches in. Critical Cloud Infrastructures Using Bayesian Network and. Markov Decision Process
... Chapter 7 CONCLUSION AND FUTURE WORK 7.1 Conclusion In this thesis, two techniques have been presented to support the conceptual approach [3] to predicting security breaches in critical cloud infrastructures. The ...
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Continuous time Markov decision process of a single aisle warehouse
... 3.2 Scope All tasks can be summarised as placing containers in and retrieving containers from the warehouse and sending containers to the break-down stations, build-up stations and outfeed. To be able to operate ...
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Optimizing credit limit policy by Markov Decision Process Models
... the Markov chain is not first ...order Markov chains. So, we tested whether the process is second-order Markov ...order Markov chain increases the size of the state space exponentially ...
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Markov Decision Process based Switching for Wireless Sensor Network
... technique. Markov Decision Process (MDP) switching algorithm has been designed for sustainable data collection tree to reduce energy consumption in the wireless sensor ...
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Optimizing Hypervideo Navigation using a Markov Decision Process Approach
... and approximations of the value function and/or of the pol- icy. The reinforcement learning approach consists in learning an optimal policy by estimating iteratively the optimal value function of the problem on the basis ...
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The Trust-Based Interactive Partially Observable Markov Decision Process
... observable Markov decision process (TI-POMDP) is developed to model the trust interactions between agents, enabling the agents to select the best course of action from the current ...observable ...
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Markov decision process algorithms for wealth allocation problems with defaultable bonds
... deterministic Markov process as introduced in Almudevar ...discrete-time Markov decision processes (MDPs), reducing the optimization problem to a discrete-time model by considering an embedded ...
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Model-based Bayesian Reinforcement Learning in Factored Markov Decision Process
... dynamic system is known and the transition probability is unknown, and actions and states are independent. In our experiments, we evaluate F-BRL using 500 simulations with 1000 steps in each simulation. We test the ...
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Time series semi-Markov decision process with variable costs for maintenance planning
... calculated in the previous iteration. As it is assumed that the final value of each state specified by the user is exact, the iterative process to find the converged value of a state used in standard MDP solutions ...
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Real Time Path Planning using a Simulation Based Markov Decision Process
... 7 Experimental Setup We have designed a set of experiments which test the MCRT technique against four of its main rivals: RRT, UCT, LSS-LRTA* and RTDP. Ten tests have been per- formed on three different game maps; each ...
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CiteSeerX — A Markov Decision Process approach with Q-learning for the stand management problem
... Preliminary experimental results are presented, that do not establish clearly the influence of stochastic factors on optimal solutions. 1 Introduction Decision aids provided to foresters by forest management ...
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Crowdsourced Software Development Process: Investigation and Modeling through Markov Decision Theory
... the process of software development at a Crowdsourced ...development process. We propose the use of Markov Decision Process to model the dynamics of the development process and ...
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A hierarchical Markov decision process modeling feeding and marketing decisions of growing pigs
... a decision support system with online data such that the system state can be found using Bayesian updating and the optimal policy of the HMDP can determine the best feeding and marketing decisions at pen ...
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A Markov Decision Process based flow assignment framework for heterogeneous network access
... The value iteration algorithm as described above is executed and updated periodically by the middleware on a device to evaluate the control policy l*(s) for the assign- ment of a flow to an access network. The middleware ...
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Cognitive Radio Jamming Mitigation using Markov Decision Process and Reinforcement Learning
... • Deceptive/Reactive jamming A deceptive jammer continuously transmits signals in order to imitate a legitimate or primary user. A reactive jammer transmits only when it detects busy channel to cause collisions. In this ...
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