partially observable markov decision process
Highly Secured Authentication and Authorization Using Partially Observable Markov Decision Process in MANETs
... a Partially Observable Markov Decision Process (POMDP) multi-armed bandit ...a process is a function of that process’s characteristics and its information ...each process, ...
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Inverse Reinforcement Learning in Partially Observable Environments
... A partially observable Markov decision process (POMDP) (Sondik, 1971; Monahan, 1982; Kaelbling et al., 1998) is a general mathematical framework for single-agent planning under uncer- ...
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Towards Relational POMDPs for Adaptive Dialogue Management
... with decision-theoretic planning. Among these, Partially Observable Markov Decision Process (POMDP) models have recently emerged as a unifying mathematical framework for dialogue ...
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On the decision rules of cost-effective treatment for patients with diabetic foot syndrome
... First we present the proposed partially observable Markov decision process (POMDP) model, and we describe and discuss its underlying data. In the following section, we construct a ...
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Model-based Bayesian Reinforcement Learning in Factored Markov Decision Process
... on Markov decision process (MDP) or partially observable Markov decision process (POMDP) is an interdisciplinary research area of machine learning, control theory, ...
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A Bayesian Approach for Learning and Planning in Partially Observable Markov Decision Processes
... dle partially observable ...the Partially Observable Markov Decision Process ...the decision- making aspect to be contingent on uncertainty over the model ...
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A POMDP Framework to Find Optimal Inspection and Maintenance Policies via Availability and Profit Maximization for Manufacturing Systems
... to decision maker's priorities. This study proposes a Partially Observable Markov Decision Process (POMDP) framework for a partially observable and stochastically ...
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Partially Observable Markov Decision Processes for Prostate Cancer Screening.
... referral decision depend on the patient’s age and PSA history? Surprisingly, there has been very little research on determining optimal decisions related to these ...a partially observable ...
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Continuous-observation partially observable semi-Markov decision processes for machine maintenance
... Partially observable semi-Markov decision processes (POS- MDPs) provide a rich framework for planning under both state transition uncertainty and observation ...maintenance decision ...
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Continuous Observation Partially Observable Semi Markov Decision Processes for Machine Maintenance
... Though the POSMDP model has existed for decades, there has been little effort in bridging the gap between POSMDP and machine maintenance. Moreover, the documented works on employing POSMDP in machine maintenance are all ...
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A Partially Observable Markov Decision for Optimal Design of Surveillance Policies for Bladder Cancer.
... The decision process is illustrated by Figure 4.1. At each decision epoch, a decision is made to either perform a cystoscopy, or to defer the decision to the next decision ...the ...
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Policy-Gradient Algorithms for Partially Observable Markov Decision Processes
... This section introduces policy-gradient methods for model-free agent training — one of the approaches we take in this thesis. Policy gradient methods compute (or estimate) the gradient of η(φ, θ) (2.1) with respect to ...
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Sequential action and beliefs under partially observable DSGE environments
... is observable and the state transition is endogenous falls into a class of ‘Markov Decision Process’ ...and observable state transition), while output production follows a ...
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Toward Automatically Measuring Learner Ability from Human Machine Dialog Interactions using Novel Psychometric Models
... management process, in order to better adapt instruction to student needs, both in terms of the level of instruction (obtained in real time through measurement models) as well as the content and dialog path ...
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Multi-task Reinforcement Learning in Partially Observable Stochastic Environments
... Dirichlet process as their common nonpara- metric prior. The Dirichlet process posterior is derived, based on a nonconventional application of Bayes ...
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On a single server queue with fixed accumulation level, state dependent service, and semi Markov modulated input flow
... Queueing process, semi-Markov process, semi-regenerative process, embedded Markov chain, semi-Markov modulated Poisson process, equilibrium, continuous time parameter process, service cy[r] ...
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Learning for Cross-layer Resource Allocation in the Framework of Cognitive Wireless Networks
... For CRNs, joint bandwidth and power allocation is the key approach to the solution of interference mitigation and network capacity optimization. Espe- cially, in a network of multiple hierarchies (e.g., DSA networks and ...
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Routing policies for a partially observable two-server queueing system
... Since Little’s Law applies to the queue lengths and the sojourn times irrespective of the policy, it is sufficient to concentrate on queue length dynamics to obtain the expec- tation of the sojourn time (system delay). ...
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Exploration vs Exploitation with Partially Observable Gaussian Autoregressive Arms
... the decision maker could have obtained from playing other arms in the multiarmed setting; from a theoretical point of view it is a Lagrange multiplier associated with the relaxed constraint that k arms have to be ...
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Emergence of Sensory Representations Using Prediction in Partially Observable Environments
... Theories on sensorimotor prediction state that an agent learns the structure of its world by learning how to predict the consequences of its actions ( [12], [2]). The sensorimotor approach proposes to learn sensor ...
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