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A Universal Dynamic Program and Refined Existence Results for Decentralized Stochastic Control
[article]
2020
arXiv
pre-print
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For sequential stochastic control problems with standard Borel measurement and control action spaces, we introduce a general (universally applicable) dynamic programming formulation, establish its well-posedness ...
In addition, new existence results are obtained for optimal policies in decentralized stochastic control. ...
Existence of Optimal Policies in Decentralized Stochastic Control and Comparison with the Literature. 5.1. New existence results in the most general form. ...
arXiv:1803.05811v4
fatcat:zmdxmugbljbstmbrn4x725wose
Hidden stochastic, quantum and dynamic information of Markov diffusion process and its evaluation by an entropy integral measure under the impulse controls actions, applied to information observer
[article]
2019
arXiv
pre-print
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Hidden information evaluates Feller kernel whose minimal path transforms Markov transition probability to probability of Brownian diffusion. ...
Each transitive transformation virtually observes origin of hidden information probabilities correlated states. IPF integrates observing Bits along minimal path assembling information Observer. ...
Since such transformation holds a Feller's kernel operator, the quantity of information, automatically selected from the Markov process by the cutoff control and measured by entropy functional during the ...
arXiv:1207.3091v4
fatcat:4zhoq3utmjcvbb7y267sbt4hea
Transformation invariant stochastic catastrophe theory
2005
Physica D : Non-linear phenomena
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From the Itô transformation rules we derive a generalized version of SCT that does remain invariant under transformation and can include Cobb's SCT as a special case. ...
Loren Cobb addressed this challenge by developing a stochastic counterpart of catastrophe theory (SCT) based on Itô stochastic differential equations. ...
Acknowledgements This research was funded by the Dutch Organization for Scientific Research (NWO), grant number 575-63-081. We are grateful to Dr. ...
doi:10.1016/j.physd.2005.08.014
fatcat:jmgnrj25bvfitjel2k4fzh5poi
ON LEBESGUE NONLINEAR TRANSFORMATIONS
2017
Bulletin of the Korean Mathematical Society
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In this paper, we introduce a quadratic stochastic operators on the set of all probability measures of a measurable space. ...
We study the dynamics of the Lebesgue quadratic stochastic operator on the set of all Lebesgue measures of the set [0, 1]. ...
The first author (N.G.) was supported by the MOHE grant FRGS14-116-0357. ...
doi:10.4134/bkms.b160212
fatcat:txiudxb2cvb7tgrls6hyljyfja
Stochastic Distance Transform
[article]
2018
arXiv
pre-print
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We, thus, define a stochastic distance transform (SDT), which has an adjustable robustness to noise. ...
Both a stochastic Monte Carlo method and a deterministic method for computing the SDT are proposed and compared. ...
Acknowledgements This work is supported by VINNOVA, MedTech4Health grants 2016-02329 and 2017-02447 and the Ministry of Education, Science, and Techn. Development of the Republic of Serbia (proj. ...
arXiv:1810.08097v1
fatcat:b5osu552yjeklo7r5jdlci2vnm
The Entropic Measure Transform
[article]
2019
arXiv
pre-print
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We introduce the entropic measure transform (EMT) problem for a general process and prove the existence of a unique optimal measure characterizing the solution. ...
The entropic measure transform is then used provide a new characterization of defaultable bond prices, forward prices, and futures prices when the asset is driven by a jump diffusion. ...
The next section compares the entropic measure transform problem with the optimal stochastic control problem proposed by Gombani and Runggaldier (2013) . ...
arXiv:1511.06032v2
fatcat:5ziwwa64rvavbdk5zghecek4ia
Generalized Transformation-based Gradient
[article]
2020
arXiv
pre-print
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2020 pre-print arXiv:1911.02681v2 fatcat:rwzyflgvxbbjll635z74d5eg7mOther Versions
In this paper, we generalized the reparameterization trick by allowing a general transformation. ...
We discover that the proposed model is a special case of control variate indicating that the proposed model can combine the advantages of CV and generalized reparameterization. ...
i (12) The polynomial-based G-TRANS gradient estimator has a form close to control variate, thus cannot be induced by any other existing generalized reparameterized gradient framework. ...
arXiv:1911.02681v3
fatcat:mszkzfzi6bhhfloadvdlmd4wie
Stochastic Simulation of Graph Transformation Systems
[chapter]
2010
Lecture Notes in Computer Science
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Simulating Stochastic Graph Transformations In order to define a general interface between the stochastic control component of the simulation and existing graph transformation tools used for executing ...
The tool is developed in Java-Eclipse, extending the VIATRA model transformation plugin with a control based on the SSJ library for Stochastic Simulation in Java. ...
doi:10.1007/978-3-642-12029-9_11
fatcat:o5xhxeppc5ht7l3okkjnwzbi54
State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning
[article]
2018
arXiv
pre-print
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We show the advantage of the SATs by considering Value-at-Risk as an example, which is a risk measure on the reward distribution instead of the measures (such as mean and variance) of the distribution. ...
In risk-sensitive scenarios, firstly we prove that, for every MDP with a stochastic transition-based reward function, there exists an MDP with a deterministic state-based reward function, such that for ...
Acknowledgments This research was supported in part by the scholarship from China Scholarship Council (CSC), and the Natural Sciences and Engineering Research Council of Canada (NSERC) under Grants 509935 ...
arXiv:1804.05950v2
fatcat:iszmjb34sjhjved4iqx44u7xmu
On the Lebesgue nonlinear transformations
[article]
2016
arXiv
pre-print
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In this paper, we introduce a quadratic stochastic operators on the set of all probability measures of a measurable space. ...
We study the dynamics of the Lebesgue quadratic stochastic operator on the set of all Lebesgue measures of the set [0,1]. Namely, we prove the regularity of the Lebesgue quadratic stochastic operators ...
Acknowledgement The work has been supported by the MOHE grant FRGS14-116-0357. ...
arXiv:1601.01757v1
fatcat:cbcnaypfgvhrbbz2mfyqv3ntka
The explicit Laplace transform for the Wishart process
[article]
2013
arXiv
pre-print
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We compare our methodology with the alternative results given by the variation of constants method, the linearization of the Matrix Riccati ODE's and the Runge-Kutta algorithm. ...
We derive the explicit formula for the joint Laplace transform of the Wishart process and its time integral which extends the original approach of Bru. ...
The Girsanov transformation is given by the following stochastic exponential (see e.g. ...
arXiv:1107.2748v5
fatcat:sptdxs4aa5dxdgimtfasjhvd34
Transform orders and stochastic monotonicity of statistical functionals
[article]
2021
arXiv
pre-print
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For this purpose, we introduce a generalized family of stochastic orders, which is referred to as transform orders, showing that it provides a flexible framework for deriving stochastic monotonicity results ...
These include some prominent inequality measures, such as the generalized entropy, the Gini index, and its generalizations. ...
For this purpose, we introduce a generalized family of
stochastic orders, generated by some reference class of functions C, denoted as transform
2
orders ...
arXiv:2112.02383v1
fatcat:nnuyb3fpefdb5gopkujvbshbr4
MeetSum: Transforming Meeting Transcript Summarization using Transformers!
[article]
2021
arXiv
pre-print
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In this paper, we utilize a Transformer-based Pointer Generator Network to generate abstract summaries for meeting transcripts. ...
Also, a qualitative analysis of the summaries generated by our model shows that these summaries and human-readable and indeed capture most of the important information from the transcripts. ...
And finally use these three values as a measurement of performance of our model.
Result
Implementation We shall measure the ROUGE-2 F 1 score using the rouge 1 library. ...
arXiv:2108.06310v1
fatcat:kcpn6w4eivhddkfucgd7ckgq6q
State-Augmentation Transformations for Risk-Sensitive Reinforcement Learning
2019
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
Preserved Fulltext
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The file type is application/pdf.
We show the advantage of the SATs by considering Value-at-Risk as an example, which is a risk measure on the reward distribution instead of the measures (such as mean and variance) of the distribution. ...
In risk-sensitive scenarios, firstly we prove that, for every MDP with a stochastic transition-based reward function, there exists an MDP with a deterministic state-based reward function, such that for ...
Acknowledgments This research was supported in part by a scholarship from China Scholarship Council (CSC), and the Natural Sciences ...
doi:10.1609/aaai.v33i01.33014512
fatcat:k5iet35okjfuxorrju7n2fcyau
Central limit theorem under uncertain linear transformations
[article]
2015
arXiv
pre-print
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We prove a variant of the central limit theorem (CLT) for a sequence of i.i.d. random variables ξ_j, perturbed by a stochastic sequence of linear transformations A_j, representing the model uncertainty ...
The limit, corresponding to a "worst" sequence A_j, is expressed in terms of the viscosity solution of the G-heat equation. ...
Denote by A t the set of stochastic process (A s ) s∈[t,1] , which are progressively measurable with respect to the minimal augmented filtration, generated by W (see Chap. 1 of [5] ), and take values ...
arXiv:1505.01084v2
fatcat:epq3gzwvp5b4jnwcq45qyevyhe
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