Relevant bibliographies by topics / Stochastic Environments

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Stochastic Environments'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

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Journal articles on the topic "Stochastic Environments"

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Tuljapurkar, Shripad. "Demography in stochastic environments." Journal of Mathematical Biology 24, no. 5 (1986): 569–81. http://dx.doi.org/10.1007/bf00275685.

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Jonzén, Ripa, and Lundberg. "A Theory of Stochastic Harvesting in Stochastic Environments." American Naturalist 159, no. 5 (2002): 427. http://dx.doi.org/10.2307/3078904.

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Jonzén, Niclas, Jörgen Ripa, and Per Lundberg. "A Theory of Stochastic Harvesting in Stochastic Environments." American Naturalist 159, no. 5 (2002): 427–37. http://dx.doi.org/10.1086/339456.

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Yoshimura, Jin, and Colin W. Clark. "Individual adaptations in stochastic environments." Evolutionary Ecology 5, no. 2 (1991): 173–92. http://dx.doi.org/10.1007/bf02270833.

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Liu, Jun. "Portfolio Selection in Stochastic Environments." Review of Financial Studies 20, no. 1 (2006): 1–39. http://dx.doi.org/10.1093/rfs/hhl001.

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Ito, Hiromu, Takashi Uehara, Satoru Morita, Kei-ichi Tainaka, and Jin Yoshimura. "Foraging behavior in stochastic environments." Journal of Ethology 31, no. 1 (2012): 23–28. http://dx.doi.org/10.1007/s10164-012-0344-y.

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Yoshimura, J., and C. W. Clark. "Individual adaptations in stochastic environments." Evolutionary Ecology 5, no. 4 (1991): 430. http://dx.doi.org/10.1007/bf02214160.

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Thattai, Mukund, and Alexander van Oudenaarden. "Stochastic Gene Expression in Fluctuating Environments." Genetics 167, no. 1 (2004): 523–30. http://dx.doi.org/10.1534/genetics.167.1.523.

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KATAGIRI, Hideki, and Masatoshi SAKAWA. "Multiobjective Optimization in Fuzzy Stochastic Environments." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 23, no. 3 (2011): 294–300. http://dx.doi.org/10.3156/jsoft.23.3_294.

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Hu, Linchao, Mugen Huang, Moxun Tang, Jianshe Yu, and Bo Zheng. "Wolbachia spread dynamics in stochastic environments." Theoretical Population Biology 106 (December 2015): 32–44. http://dx.doi.org/10.1016/j.tpb.2015.09.003.

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Dissertations / Theses on the topic "Stochastic Environments"

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Uyar, Emrah. "Routing in stochastic environments." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/26554.

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Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.<br>Committee Co-Chair: Erera, Alan L.; Committee Co-Chair: Savelsbergh, Martin W. P.; Committee Member: Ergun, Ozlem; Committee Member: Ferguson, Mark; Committee Member: Kleywegt, Anton J.. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Schmidt, Christian. "Evolutionary computation in stochastic environments." Karlsruhe Univ.-Verl. Karlsruhe, 2007. http://www.uvka.de/univerlag/volltexte/2007/231/.

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Cao, Jie. "Stochastic inventory control in dynamic environments." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0011469.

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Godany, M. "Evolution of chemotaxis in stochastic environments." Thesis, University College London (University of London), 2016. http://discovery.ucl.ac.uk/1530046/.

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Most of our understanding of bacterial chemotaxis comes from studies of Escherichia coli. However, recent evidence suggests significant departures from the E. coli paradigm in other bacterial species. In the first part of this work, we argue that the observed departures may stem from different species inhabiting distinct environments and thus adapting differently to specific environmental pressures. We therefore study the performance of various chemotactic strate¬gies under a range of stochastic time- and space-varying attractant distributions in silico. We describe a novel type of response in
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Agakov, Felix. "Variational information maximization in stochastic environments." Thesis, University of Edinburgh, 2006. http://hdl.handle.net/1842/28343.

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Information maximization is a common framework of unsupervised learning, which may be used for extracting informative representations of the observed patterns. The key idea there is to maximize mutual information (MI), which is a formal measure of coding efficiency. Unfortunately, exact maximization of MI is computationally tractable only in a few special cases; more generally, approximations need to be considered. We describe a family of variational lower bounds on mutual information which gives rise to a formal and theoretically rigorous approach to information maximization in large-scale st
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Ma, Fangchang. "On maximum-reward motion in stochastic environments." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98696.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2015.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 75-77).<br>In this thesis, we consider the problem of an autonomous mobile robot operating in a stochastic reward field to maximize total rewards collected in an online setting. This is a generalization of the problem where an unmanned aerial vehicle (UAV) collects data from randomly deployed unattended ground sensors (UGS). Specifically, the rewards are assumed to be generated by a Poisson point process. T
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Mondschein, Susana V. "Optimal sales strategies in stochastic, dynamic environments." Thesis, Massachusetts Institute of Technology, 1993. http://hdl.handle.net/1721.1/12733.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.<br>Includes bibliographical references (leaves 132-134).<br>by Susana V. Mondschein.<br>Ph.D.
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Cheng, Tak Sum. "Stochastic optimal control in randomly-branching environments." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/713.

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Ortgiese, Marcel. "Stochastic processes in random environment." Thesis, University of Bath, 2009. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507234.

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We are interested in two probabilistic models of a process interacting with a random environment. Firstly, we consider the model of directed polymers in random environment. In this case, a polymer, represented as the path of a simple random walk on a lattice, interacts with an environment given by a collection of time-dependent random variables associated to the vertices. Under certain conditions, the system undergoes a phase transition from an entropy-dominated regime at high temperatures, to a localised regime at low temperatures. Our main result shows that at high temperatures, even though
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Schmidt, Christian [Verfasser]. "Evolutionary computation in stochastic environments / von Christian Schmidt." Karlsruhe : Univ.-Verl. Karlsruhe, 2007. http://d-nb.info/984871349/34.

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Books on the topic "Stochastic Environments"

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Yoshimura, Jin, and Colib W. Clark, eds. Adaptation in Stochastic Environments. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-51483-8.

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Schmidt, Christian. Evolutionary computation in stochastic environments. Univ.-Verl. Karlsruhe, 2006.

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Smunt, Timothy L. Lot splitting in stochastic flow shop and job shop environments. University of Illinois at Urbana-Champaign, 1993.

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Oliehoek, Frans A. Value-based planning for teams of agents in stochastic partially observable environments. Amsterdam University Press, 2010.

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Hughes, B. D. Random walks and random environments. Clarendon Press, 1995.

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Benth, Fred Espen. Stochastics of Environmental and Financial Economics. Springer Nature, 2015.

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Benth, Fred Espen, and Giulia Di Nunno, eds. Stochastics of Environmental and Financial Economics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-23425-0.

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Atta-Mensah, Joseph. The demand for money in a stochastic environment. Bank of Canada, 2004.

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Hipel, Keith W., ed. Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1072-3.

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Hipel, Keith W., and Liping Fang, eds. Stochastic and Statistical Methods in Hydrology and Environmental Engineering. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-3081-5.

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Book chapters on the topic "Stochastic Environments"

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Wiesenfeld, Kurt, Thomas Wellens, and Andreas Buchleitner. "Stochastic Resonance." In Coherent Evolution in Noisy Environments. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45855-7_3.

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Carpin, Stefano, and Andreas Birk. "Stochastic Map Merging in Rescue Environments." In RoboCup 2004: Robot Soccer World Cup VIII. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/978-3-540-32256-6_43.

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Audibert, Jean-Yves, Rémi Munos, and Csaba Szepesvári. "Tuning Bandit Algorithms in Stochastic Environments." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-75225-7_15.

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Orseau, Laurent, Tor Lattimore, and Marcus Hutter. "Universal Knowledge-Seeking Agents for Stochastic Environments." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40935-6_12.

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Hazel, Wade N., and Richard Smock. "Modeling Selection on Conditional Strategies in Stochastic Environments." In Lecture Notes in Biomathematics. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-51483-8_8.

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Enright, John J., Emilio Frazzoli, Marco Pavone, and Ketan Savla. "UAV Routing and Coordination in Stochastic, Dynamic Environments." In Handbook of Unmanned Aerial Vehicles. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-90-481-9707-1_28.

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Zöller, Nikolas. "Entropy Production in Inhomogeneous Thermal Environments." In Optimization of Stochastic Heat Engines in the Underdamped Limit. Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-16350-1_5.

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Pinciroli, Riccardo, Marco Gribaudo, and Giuseppe Serazzi. "Modeling Multiclass Task-Based Applications on Heterogeneous Distributed Environments." In Analytical and Stochastic Modelling Techniques and Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61428-1_12.

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Beissinger, Steven R., and James P. Gibbs. "Are Variable Environments Stochastic? A Review of Methods to Quantify Environmental Predictability." In Lecture Notes in Biomathematics. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-51483-8_7.

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Zhou, Zhengyuan, Nicholas Bambos, and Peter Glynn. "Dynamics on Linear Influence Network Games Under Stochastic Environments." In Lecture Notes in Computer Science. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-47413-7_7.

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Conference papers on the topic "Stochastic Environments"

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Herb, Tobias, Tim Jungnickel, and Christoph Alt. "Weak consistency and stochastic environments." In EuroSys '16: Eleventh EuroSys Conference 2016. ACM, 2016. http://dx.doi.org/10.1145/2911151.2911161.

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Miura, Shuwa, Andrew L. Cohen, and Shlomo Zilberstein. "Maximizing Legibility in Stochastic Environments." In 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN). IEEE, 2021. http://dx.doi.org/10.1109/ro-man50785.2021.9515318.

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Chiang, Hao-Tien, Nathanael Rackley, and Lydia Tapia. "Stochastic Ensemble Simulation motion planning in stochastic dynamic environments." In 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2015. http://dx.doi.org/10.1109/iros.2015.7353916.

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Gießen, Christian, and Timo Kötzing. "Robustness of populations in stochastic environments." In GECCO '14: Genetic and Evolutionary Computation Conference. ACM, 2014. http://dx.doi.org/10.1145/2576768.2598227.

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Atanasov, Nikolay, Jerome Le Ny, Nathan Michael, and George J. Pappas. "Stochastic source seeking in complex environments." In 2012 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2012. http://dx.doi.org/10.1109/icra.2012.6225289.

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Nguyen, Thinh, Dong Nguyen, and Duc Tran. "Stochastic Binary Sensor Networks for Noisy Environments." In 2006 First International Conference on Communications and Electronics. IEEE, 2006. http://dx.doi.org/10.1109/cce.2006.350856.

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Saisubramanian, Sandhya, Kyle Hollins Wray, Luis Pineda, and Shlomo Zilberstein. "Planning in Stochastic Environments with Goal Uncertainty." In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2019. http://dx.doi.org/10.1109/iros40897.2019.8967718.

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Millet, Christophe, and Christophe Haynes. "Stochastic Model Approach of Meteor-Generated Infrasound." In AIAA Atmospheric and Space Environments Conference. American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-7999.

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Blanchard, Ph, D. Volchenkov, Christopher C. Bernido, and M. Victoria Carpio-Bernido. "Exploring Urban Environments By Random Walks." In STOCHASTIC AND QUANTUM DYNAMICS OF BIOMOLECULAR SYSTEMS: Proceedings of the 5th Jagna International Workshop. AIP, 2008. http://dx.doi.org/10.1063/1.2956796.

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Su, Xiao, Zhenzhen Ye, Lingshuang Wu, and Yi Shang. "Optimal Stochastic Media Storage in Federated Cloud Environments." In 2020 International Conference on Computing, Networking and Communications (ICNC). IEEE, 2020. http://dx.doi.org/10.1109/icnc47757.2020.9049482.

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Reports on the topic "Stochastic Environments"

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Cassandras, Christos G. Real-Time Optimization in Complex Stochastic Environments. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada564171.

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Shaukat, Kamran. A study of Leslie model under stochastic environments. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.3109.

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Castanon, David A., and Christos G. Cassandras. Distributed Mission Control for Unmanned Air Vehicles in Stochastic Environments. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada567152.

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Carin, Lawrence, Leslie Collins, Qing Liu, et al. Adaptive Multi-Modality Inverse Scattering for Targets Embedded in General Stochastic Environments. Defense Technical Information Center, 2008. http://dx.doi.org/10.21236/ada519818.

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Aines, R., J. Nitao, R. Newmark, et al. The Stochastic Engine Initiative: Improving Prediction of Behavior in Geologic Environments We Cannot Directly Observe. Office of Scientific and Technical Information (OSTI), 2002. http://dx.doi.org/10.2172/15002143.

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Majda, Andrew J., John Harlim, Samuel Stechmann, Duane E. Waliser, and Dimitrios Giannakis. Physics Constrained Stochastic-Statistical Models for Extended Range Environmental Prediction. Defense Technical Information Center, 2014. http://dx.doi.org/10.21236/ada615968.

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Baumann, William T., Richard L. Moose, Hugh F. VanLandigham, Mauro J. Caputi, Stephen H. Jones, and Bhaskar Gorti. Active Control of Generalized Complex Modal Structures in a Stochastic Environment. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada251910.

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Majda, Andrew J. Report: Physics Constrained Stochastic Statistical Models for Extended Range Environmental Prediction. Defense Technical Information Center, 2013. http://dx.doi.org/10.21236/ada601833.

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Majda, Andrew J. Report: Physics Constrained Stochastic Statistical Models for Extended Range Environmental Prediction. Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada590513.

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Engle, Robert, and Joshua Rosenberg. Hedging Options in a GARCH Environment: Testing the Term Structure of Stochastic Volatility Models. National Bureau of Economic Research, 1994. http://dx.doi.org/10.3386/w4958.

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