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TeXDYNA: Hierarchical Reinforcement Learning in Factored MDPs [chapter]

Olga Kozlova, Olivier Sigaud, Christophe Meyer
2010 Lecture Notes in Computer Science  
In this paper, we present TeXDYNA, an algorithm designed to solve large reinforcement learning problems with unknown structure by integrating hierarchical abstraction techniques of Hierarchical Reinforcement  ...  Reinforcement learning is one of the main adaptive mechanisms that is both well documented in animal behaviour and giving rise to computational studies in animats and robots.  ...  -The localization of the models results in an exponential reduction of the state-action space of each option.  ... 
doi:10.1007/978-3-642-15193-4_46 fatcat:5moziwlpdnantdq4dp5qim4k34

Data-Driven Performance Analysis of Scheduled Processes [chapter]

Arik Senderovich, Andreas Rogge-Solti, Avigdor Gal, Jan Mendling, Avishai Mandelbaum, Sarah Kadish, Craig A. Bunnell
2015 Lecture Notes in Computer Science  
The projection is facilitated by a sequence of folding operations that alter the structure and dynamics of the Petri Net model.  ...  In this work, we address this gap by developing a novel method for utilizing rich process logs to analyze performance of scheduled processes.  ...  Valery Trofimov, Igor Gavako and Ella Nadjharov, for their help with data analysis. We also thank Kristen Camuso, from Dana-Faber Cancer Institute for the insightful data discussions.  ... 
doi:10.1007/978-3-319-23063-4_3 fatcat:l6ls72jwavg4xj6uzjv3p7wi3e

Discovery Radiomics for Multi-Parametric MRI Prostate Cancer Detection [article]

Audrey G. Chung, Mohammad Javad Shafiee, Devinder Kumar, Farzad Khalvati, Masoom A. Haider, Alexander Wong
2015 arXiv   pre-print
Discovery radiomics aims to uncover abstract imaging-based features that capture highly unique tumour traits and characteristics beyond what can be captured using predefined feature models.  ...  methods help streamline the process and has the potential to significantly improve diagnostic accuracy and efficiency, and thus improving patient survival rates.  ...  FK and MH were involved in collecting and reviewing the data. All authors contributed to the writing and reviewing of the paper.  ... 
arXiv:1509.00111v3 fatcat:ysou3y4m5bbeliq7o7nz2t7mli

Stochastic Quantization and the LargeNLimit of Quantum Field Theories

Jorge Alfaro
1993 Progress of Theoretical Physics Supplement  
We rely on the Langevin and Fokker-Planck approaches to stochastic processes.  ...  Important properties of this limit such as the Eguchi-Kawai reduction and the master field idea are discussed in detail, illustrated by several examples.  ...  This work has been partially supported by FONDECYT 91-0634.  ... 
doi:10.1143/ptps.111.401 fatcat:474avypmgneubes6ieo5x6jjky

Automated Deep Abstractions for Stochastic Chemical Reaction Networks [article]

Tatjana Petrov, Denis Repin
2020 arXiv   pre-print
A recently proposed abstraction method uses deep learning to replace this CTMC with a discrete-time continuous-space process, by training a mixture density deep neural network with traces sampled at regular  ...  process.  ...  abstract discrete time stochastic process overS.  ... 
arXiv:2002.01889v1 fatcat:623bkhtxgfbdzhoe77ochltoma

Preface to the special issue on Probabilistic Model Checking

Christel Baier, Marta Kwiatkowska
2013 Formal methods in system design  
properties for Markov chains and Markov decision processes.  ...  Quantitative model checking algorithms, where the actual probability value is computed, were formulated in 1990s by Courcoubetis and Yannakakis [7], Hansson and Johnsson [9], Bianco and de Alfaro [4] and  ...  In [11] , game semantics is applied to obtain a compositional fully-abstract method for establishing equivalence between probabilistic call-by-value programs.  ... 
doi:10.1007/s10703-013-0194-4 fatcat:neeu3chulzhtthtdlvatjawmxy

Modelling an Ammonium Transporter with SCLS

Mario Coppo, Ferruccio Damiani, Elena Grassi, Mike Guether, Angelo Troina
2009 Electronic Proceedings in Theoretical Computer Science  
In this work we apply SCLS to model a newly discovered ammonium transporter.  ...  The initial simulation results of the modelling of the symbiosis process are promising and indicate new directions for biological investigations.  ...  In this work we apply SCLS to model a newly discovered ammonium transporter.  ... 
doi:10.4204/eptcs.6.6 fatcat:6b2qgscfvvf6dnbaqcsspvgg2u

Stochastic-Aware Conformance Checking: An Entropy-Based Approach [chapter]

Sander J. J. Leemans, Artem Polyvyanyy
2020 Lecture Notes in Computer Science  
Artem Polyvyanyy was partly supported by the Australian Research Council Discovery Project DP180102839.  ...  by considering the SDFAs of an event log and a stochastic process model.  ...  Model S 1 was discovered by a stochastic process discovery technique [11] from L. Model S 2 is a manually created SPN that is similar to S 1 but has different probabilities.  ... 
doi:10.1007/978-3-030-49435-3_14 fatcat:egd3babphrb67nowpqj4yywoua

Techniques for Analysis and Calibration of Multi-agent Simulations [chapter]

Manuel Fehler, Franziska Klügl, Frank Puppe
2005 Lecture Notes in Computer Science  
In this paper we present analysis and calibration techniques that exploit knowledge about a multi agent society in order to calibrate the system parameters of a corresponding society simulation model.  ...  typical problems of multi agent simulation calibration like the vast amount of parameters that need to be calibrated, the complex parameter dependencies due to interactions between the simulated agents and  ...  Acknowledgement The work described in this paper was supported by DFG under SFB 554(D3/4) "Emergent Behavior in Superorganisms"  ... 
doi:10.1007/11423355_22 fatcat:zl3vmc25ergxbmr6ed3k7slqe4

Abstraction and Training of Stochastic Graph Transformation Systems [chapter]

Mayur Bapodra, Reiko Heckel
2013 Lecture Notes in Computer Science  
In this paper, we aim to simplify models by abstraction while preserving relevant trends in their global behaviour.  ...  Based on a hierarchical graph model inspired by membrane systems, structural abstraction is achieved by "zooming out" of membranes, hiding their internal state.  ...  This process is known as inference in a BN. 6. Test the parameters by running stochastic simulations of SGT S 2 .  ... 
doi:10.1007/978-3-642-37057-1_23 fatcat:czdhcwchzndgdglfe46mi6wbai

Building fast Bayesian computing machines out of intentionally stochastic, digital parts [article]

Vikash Mansinghka, Eric Jonas
2014 arXiv   pre-print
We find that by connecting stochastic digital components according to simple mathematical rules, one can build massively parallel, low precision circuits that solve Bayesian inference problems and are  ...  Here we show how to build fast Bayesian computing machines using intentionally stochastic, digital parts, narrowing this efficiency gap by multiple orders of magnitude.  ...  Acknowledgements The authors would like to acknowledge Tomaso Poggio, Thomas Knight, Gerald Sussman, Rakesh Kumar and Joshua Tenenbaum for numerous helpful discussions and comments on early drafts, and  ... 
arXiv:1402.4914v1 fatcat:mnjmxywzyrgo5avrttcvsxosri

Guest editorial: special issue on formal methods in control

Necmiye Ozay, Paulo Tabuada
2017 Discrete event dynamic systems  
After a thorough review process, six full papers and two short papers were selected to appear in the special issue. The topics cov-Necmiye Ozay  ...  Acknowledgements The guest editors wish to thank all the authors, for their submissions, and the reviewers, for their timely and careful evaluation of the submitted papers.  ...  The paper by Zamani et al. addresses the scalability problem for abstraction based control synthesis for stochastic systems.  ... 
doi:10.1007/s10626-017-0246-9 fatcat:7pbowztuabfj7gbklwbcbrv6oq

Biology as reactivity

Jasmin Fisher, David Harel, Thomas A. Henzinger
2011 Communications of the ACM  
the description and analysis of reactive systems can help in the process of biological discovery, ultimately by providing biologists with virtual experimentation environments.  ...  among which are the varieties of temporal logic 63 and process algebra. 57 Scenario-based languages have been used to model biology too, such as live sequence charts (LSC). 19 All of this, in turn, has  ...  We would like to thank our past collaborators on these topics, for the wisdom and ideas they have contributed to us over the years.  ... 
doi:10.1145/2001269.2001289 fatcat:4gt5hy3wrfes5ejmotpchklhqi

Computational Models of the NF-KB Signalling Pathway

Richard Williams, Jon Timmis, Eva Qwarnstrom
2014 Computation  
NF-κB is a transcription factor, which is ubiquitous within cells and controls a number of immune responses, including inflammation and apoptosis.  ...  There have been a number of computational (mathematical) models developed of the signalling pathway over the past decade.  ...  et al., Yde et al., Longo et al. and Zambrano et al., along with the model reduction algorithm developed by West et al.  ... 
doi:10.3390/computation2040131 fatcat:urj5g3k3dfghhkiwqzu5mdxxgq

To do things with words (only): An introduction to the role of noise in coordination dynamics without equations [article]

Julien Lagarde
2017 arXiv   pre-print
physics of Brownian motion and stochastic processes.  ...  The relations between those theories/ concepts have been drawn for some cases in their original fields, for example between free energy minimization and diffusion model in a force field (Jordan et al.,  ...  Acknowledgements: The author is indebted to Scott Kelso and Viktor Jirsa for their contributions to the interdisciplinary PhD training program proposed at the Center for complex systems and Brain Sciences  ... 
arXiv:1702.02492v1 fatcat:dfmv4rewgrbsxfc6ralo5jmqnm
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