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Books on the topic 'Foundation reinforcement'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

J, Bowders John, Scranton Heather B, Broderick Gregory P, American Society of Civil Engineers. Geo-Institute. Geosynthetics Committee., and Geo-Congress 98 (1998 : Boston, Mass.), eds. Geosynthetics in foundation reinforcement and erosion control systems: Proceedings of sessions of Geo-Congress. American Society of Civil Engineers, 1998.

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2

Geo-Congress 98 (1998 Boston, Mass.). Geosynthetics in foundation reinforcement and erosion control systems: Proceedings of sessions of Geo-Congress 98. American Society of Civil Engineers, 1998.

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3

Norihiko, Miura, and Yamanouchi Toyotoshi, eds. Geosynthetic reinforcement in foundations. Elsevier Science Publishers, 1990.

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4

I, Feklin V., and Ginzburg L. K, eds. Reinforcement and reconstruction of foundations. A.A. Balkema, 1996.

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5

Bhandari, Jalaj. Optimization Foundations of Reinforcement Learning. [publisher not identified], 2020.

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6

Zhao, Shiyu. Mathematical Foundations of Reinforcement Learning. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-3944-8.

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7

Chaddock, B. C. J. Deformation of road foundations with geogrid reinforcement. Transport and Road Reseach Laboratory, Highways Group, Pavement Design and Maintenance Division, 1988.

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8

McLean, David I. Seismic performance of bridge columns with interlocking spiral reinforcement. Washington State Dept. of Transportation, 1994.

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9

Leonovich, Sergey, Nikolay Chernoivan, Viktor Tur, and Dmitriy Litvinovskiy. Technology of reconstruction of buildings and structures. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1867636.

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The monograph provides the basics of technology for the production of general construction and finishing works performed during the reconstruction of existing industrial and civil facilities: strengthening and restoration of exploited structures, as well as the construction of new buildings and structures designed at the reconstructed facility. The issues of conducting field surveys of operated buildings and structures in order to prepare a conclusion on the technical condition of load-bearing and enclosing structures are considered. The main design solutions and technology of work

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10

J, Bowders John, Scranton Heather B, Broderick Gregory P, American Society of Civil Engineers. Geo-Institute. Geosynthetics Committee., and Geo-Congress (1998 : Boston, Mass.), eds. Geosynthetics in foundation reinforcemnt and erosion control systems: Proceedings of the sessions of the Geo-Congress 98 sponsored by the Geosynthetics Committee of the Geo-Institute of the American Society of Civil Engineers, October 18-21, 1998, Boston, Massachusetts. American Society of Civil Engineers, 1998.

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11

Mathematical Foundation of Reinforcement Learning. Springer, 2024.

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12

Colin J. F. P. Jones. Earth reinforcement and soil structures. Butterworths, 1988.

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13

Bell, F. G., and Colin J. F. P. Jones. Earth Reinforcement and Soil Structures. Elsevier Science & Technology Books, 2013.

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14

Bull, Larry, and Tim Kovacs. Foundations of Learning Classifier Systems. Springer Berlin / Heidelberg, 2010.

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15

Foundations of Reinforcement Learning with Applications in Finance. Unknown Publisher, 2022.

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16

Foundations of Reinforcement Learning with Applications in Finance. Unknown Publisher, 2022.

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17

Jelvis, Tikhon, and Ashwin Rao. Foundations of Reinforcement Learning with Applications in Finance. Taylor & Francis Group, 2022.

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18

Jelvis, Tikhon, and Ashwin Rao. Foundations of Reinforcement Learning with Applications in Finance. Taylor & Francis Group, 2022.

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19

Jelvis, Tikhon, and Ashwin Rao. Foundations of Reinforcement Learning with Applications in Finance. Taylor & Francis Group, 2022.

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20

Albrecht, Stefano V., and Filippos Christianos. Multi-Agent Reinforcement Learning: Foundations and Modern Approaches. MIT Press, 2024.

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21

Graesser, Laura, and Wah Loon Keng. Foundations of Deep Reinforcement Learning: Theory and Practice in Python. Pearson Education, Limited, 2020.

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22

Graesser, Laura, and Wah Loon Keng. Foundations of Deep Reinforcement Learning: Theory and Practice in Python. Addison-Wesley Professional, 2019.

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23

Graesser, Laura, and Wah Loon Keng. Foundations of Deep Reinforcement Learning: Theory and Practice in Python. Pearson Education, Limited, 2021.

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24

(Editor), Larry Bull, and Tim Kovacs (Editor), eds. Foundations of Learning Classifier Systems (Studies in Fuzziness and Soft Computing) (Studies in Fuzziness and Soft Computing). Springer, 2005.

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25

Buckingham, Grant Cyrus. Seismic performance of bridge columns with interlocking spiral reinforcement. 1992.

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26

Lloyd, Christopher, and Tim Battin. Reinforcements for the Wage-Earners’ Welfare State? Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198779599.003.0009.

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The characterization of Australia as a wage-earners’ welfare state (Frank Castles) has encouraged some scholars to argue that the Australian model remained necessarily labourist and incapable of developing in a social democratic direction. This chapter shows that World War I had a far-reaching effect on the scale of Australia’s welfare state, and that World War II profoundly changed both its scale and structure in a more social democratic direction. Australia’s federal system and its written constitution have constrained centralist and socialist initiatives, particularly desired by the Austral

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27

Mass.) Asce Geo-Congress (1998 Boston and Mass.) Geo-Congress (1998 : Boston. Geosynthetics in Foundation Reinforcemnt and Erosion Control Systems: Proceedings of Sessions of the Geo-Congress 98 : October 18-21, 1998 Boston, Massachusetts (Geotechnical Special Publication). American Society of Civil Engineers, 1998.

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28

Recommendations For Design And Analysis Of Earth Structures Using Geosynthetic Reinforcements Ebgeo. Wiley-VCH Verlag GmbH, 2011.

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29

Mungol, Neelesh. Mastering Reinforcement Learning : from Foundations to Frontiers: Unleashing the Power of Trial-And-Error Learning for Artificial Intelligence. Absolute Author Publishing House, 2023.

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30

Heng, Liao, and Bill McColl, eds. Mathematics for Future Computing and Communications. Cambridge University Press, 2021. http://dx.doi.org/10.1017/9781009070218.

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For 80 years, mathematics has driven fundamental innovation in computing and communications. This timely book provides a panorama of some recent ideas in mathematics and how they will drive continued innovation in computing, communications and AI in the coming years. It provides a unique insight into how the new techniques that are being developed can be used to provide theoretical foundations for technological progress, just as mathematics was used in earlier times by Turing, von Neumann, Shannon and others. Edited by leading researchers in the field, chapters cover the application of new mat

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