Results 261 to 270 of about 57,303 (303)
A Comparison of Methods for Modeling Multistate Cancer Progression Using Screening Data with Censoring after Intervention. [PDF]
Med Decis MakingAkwiwu EU +3 more
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In Silico Evaluation of Algorithm-Based Clinical Decision Support Systems Based on Care Pathway Simulation Models: Scoping Review. [PDF]
JMIR AIDorosan M +4 more
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An Entropy-Based Framework for Hybrid Coalitions in Game Theory-Part I: Human Arbitration. [PDF]
Entropy (Basel)Sepúlveda-Fontaine SA, Amigó JM.
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A Bumblebee-Inspired Spatial Memory Navigation Framework for Robotic Odor Source Localization. [PDF]
Biomimetics (Basel)Xu T, Guo Y, Wu Z, Wu J.
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Statistica Neerlandica, 1985
AbstractA review is presented of the development over the years of the theory and practical use of Markov decision processes. To this purpose three periods are considered: before 1966, from 1966 till 1972, and after 1973. In all 3 periods there has been some contribution from the Netherlands, but particularly in the last period the research in the ...
Wal, van der, J., Wessels, J.
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AbstractA review is presented of the development over the years of the theory and practical use of Markov decision processes. To this purpose three periods are considered: before 1966, from 1966 till 1972, and after 1973. In all 3 periods there has been some contribution from the Netherlands, but particularly in the last period the research in the ...
Wal, van der, J., Wessels, J.
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On the Generation of Markov Decision Processes
Journal of the Operational Research Society, 1995Summary: Comparisons of the performance of solution algorithms for Markov decision processes rely heavily on problem generators to provide sizeable sets of test problems. Existing generation techniques allow little control over the properties of the test problems and often result in problems which are not typical of real-world examples.
Archibald, T. W. +2 more
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Online Markov Decision Processes
Mathematics of Operations Research, 2009We consider a Markov decision process (MDP) setting in which the reward function is allowed to change after each time step (possibly in an adversarial manner), yet the dynamics remain fixed. Similar to the experts setting, we address the question of how well an agent can do when compared to the reward achieved under the best stationary policy over ...
Eyal Even-Dar +2 more
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Monotonicity in a Markov Decision Process
Mathematics of Operations Research, 1988Concavity of optimal costs and monotonicity of optimal actions are established for a Markov decision problem in which state space and action space are ordered, but in which the cost functions do not possess properties commonly used to establish monotonicity.
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Risk-Constrained Markov Decision Processes
IEEE Transactions on Automatic Control, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Vivek S. Borkar, Rahul Jain 0002
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