Relevant bibliographies by topics / Mixed reinforcement

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Academic literature on the topic 'Mixed reinforcement'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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Journal articles on the topic "Mixed reinforcement"

Alaee, Pooya, Yoshiharu Sato, and Bing Li. "Drift capacity of high-strength concrete columns with mixed-grade longitudinal reinforcements." Advances in Structural Engineering 22, no. 2 (August 16, 2018): 519–34. http://dx.doi.org/10.1177/1369433218794270.

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A unique reinforced concrete column design method which aims to improve the ductile behavior of reinforced concrete columns by utilizing various steel grades for longitudinal reinforcements is evaluated in this article. Six large-scale reinforced concrete columns were tested, with the columns subjected to axial load and cyclic forces under reversed bending. The parameters varied in the test program including the axial loading level and the ratio and strength of longitudinal steel reinforcement. It was found from the test results that utilizing longitudinal high-strength steel reinforcement by the ratio of 30%, 50%, and 100% of the total longitudinal reinforcement in a column section will increase the lateral loading drift capacity by 18%, 26%, and 55% on average, respectively. Parametric studies via nonlinear finite-element approach were performed to study the influence of various design parameters on the ultimate drift capacity of reinforced concrete columns. The correlation between the ultimate drift capacity and the confinement level, the axial loading level, and the ratio and grade of longitudinal high-strength reinforcing bars was investigated. Design charts for various ultimate drift levels in terms of other design parameters were developed.

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Ovalı, İsmail, Cemal Esen, Sevda Albayrak, and Halil Karakoç. "Effect of Gr Contents on Wear Properties of Al2024/MgO/Al2O3/Gr Hybrid Composites." MATEC Web of Conferences 167 (2018): 02010. http://dx.doi.org/10.1051/matecconf/201816702010.

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In the present study, hybrid metal matrix composites, Al2024/10Al2O3, Al2024/10Al2O3/3MgO, Al2024/10Al2O3/6MgO, Al2024/10Al2O3/3MgO/1.5 Gr, Al2024/10Al2O3/3MgO/3Gr, and reinforcement samples (AA 2024) produced with powder metallurgy process. AA 2024 and reinforcement powders were determined mixture rations and separately mixed during 30 minutes in a three-dimensional Turbula mixer. The mixed compositions were pressed at 300 MPa and sintered at 550°C during 1 h. After that, three materials were extruded at the same temperature. Experimental results show that hybrid metal matrix composites (HMMCs) a better wear resistance than the reinforcement samples because of higher hardness. Gr behave as a lubricant during wear process. The wear resistance of HMMCs can be optimized with controlling of the reinforcement content and type.

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Chen, Gang, Shuai Yuan, Yu Bo Peng, and Wei Jun Yang. "Study of the Combined Effect of Steel Reinforcement and Expansion Agent on the Crack Resistance of Ready-Mixed Concrete." Applied Mechanics and Materials 204-208 (October 2012): 1159–63. http://dx.doi.org/10.4028/www.scientific.net/amm.204-208.1159.

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The objective of this work is to find the law of combined effect of steel reinforcement and expansion agent (EA) on the crack resistance of ready-mixed concrete by doing flat-plate method experimental study on the crack resistance of ready-mixed concrete with EA, also with EA and steel reinforcement, with a deep analysis of the mechanism of reinforcement and EA on ready-mixed concrete. The paper comes to the role of ready-mixed concrete cracking performance which is influenced by reinforcement steel and EA.

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Zhou, Jun Long, Zhong Wen Ou, Qiao Chen, and Yun Chen. "The Influence of Admixtures on the Corrosion Protection Afforded Steel Reinforcement in Seawater-and-Seasand Concrete." Advanced Materials Research 250-253 (May 2011): 81–89. http://dx.doi.org/10.4028/www.scientific.net/amr.250-253.81.

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It is inevitable for steel reinforcement to be corroded when mixed with seawater-and-seasand concrete. In order to improve steel corrosion protection properties of seawater-and-seasand concrete, reduce the chloride ion’s attack on steel reinforcement in structural concrete and lengthen the steel reinforcement’s service time, this paper presents an experimental study on whether admixtures like fly ash, slag and metakaolin in the seawater-and-seasand could retard the corrosion to steel reinforcement and provide protection to steel reinforcement in seawater-and-seasand concrete. The results indicated that metakaolin had a significant anti-corrosion effect and greatly enhanced the steel corrosion protection properties of seawater-and-seasand concrete whereas both fly ash and slag did not appear to have any obvious influence on curbing the corrosion of steel reinforcement.

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MAKIUCHI, Katsuhiko, Kunio MINEGISHI, and In Ho CHOI. "Reinforcement Effects of Soil mixed with Fibers." Proceedings of geosynthetics symposium 11 (1996): 37–44. http://dx.doi.org/10.5030/jcigsjournal1995.11.37.

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Alsop, Brent, and Michael Davison. "PREFERENCE FOR MULTIPLE VERSUS MIXED SCHEDULES OF REINFORCEMENT." Journal of the Experimental Analysis of Behavior 45, no. 1 (January 1986): 33–45. http://dx.doi.org/10.1901/jeab.1986.45-33.

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Steinhauer, Gene D. "Behavioral Contrast on Mixed Schedules." Psychological Reports 78, no. 2 (April 1996): 673–74. http://dx.doi.org/10.2466/pr0.1996.78.2.673.

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Keypecking by 4 pigeons was studied on mixed schedules of reinforcement. Positive behavioral contrast was found when the schedule was shifted from Mixed VI VI to Mixed VI Extinction only when the VI schedule value was small relative to the component duration.

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Keehn, J. D., and Emoke Stoyanov. "Adjunctive Drinking in a Mixed Reinforcement Schedule: Effect of Reinforcement Magnitude on Schedule-Induced Polydipsia." Psychological Record 36, no. 4 (October 1986): 553–61. http://dx.doi.org/10.1007/bf03394973.

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Bova, Y., and O. Kashoyida. "METHOD OF CALCULATION HOLLOW (CAISSON) SLABS WITH MIXED REINFORCEMENT." Building constructions. Theory and Practice, no. 2 (March 30, 2018): 92–98. http://dx.doi.org/10.32347/2522-4182.2.2018.92-98.

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孔, 恒. "Study on Indoor Reinforcement Treatment of Waste Mixed Soil." Hans Journal of Civil Engineering 08, no. 04 (2019): 872–80. http://dx.doi.org/10.12677/hjce.2019.84101.

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Dissertations / Theses on the topic "Mixed reinforcement"

Scopes, Peter D. "Automated mixed resolution acyclic tiling in reinforcement learning." Thesis, University of York, 2015. http://etheses.whiterose.ac.uk/16279/.

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This thesis presents novel work on how to automatically alter a Tile Coding whilst simultaneously learning to improve both the quality of an agent’s policy and its speed of learning. It also identifies the detrimental effects of transition cycles in an MDP to Reinforcement Learning and Tile Coding. Reinforcement Learning (RL) (Sutton and Barto 1998) is a popular and widely-studied ma- chine learning technique, where an agent learns a policy through continual interactions with an environment, based on performing actions and observing their rewards. In the basic RL formulation, in order to guarantee learning an optimal policy, an agent needs to visit each state in the environment at least once (and often repeatedly). For this reason the speed of learning does not scale well to complex environments with large state spaces. Tile Coding (TC) (Albus 1981) is a popular value function approximation method that is able to reduce the size of a state space through approximation. In this approach, values from one or more state features are grouped into exhaustive partitions called tiles. However, as the state space becomes more granular, there is an increase of potential reduction in the precision and quality of the policy the agent is learning. As a rule of thumb, the larger the tiles are in a tiling, the faster the agent arrives at its final policy but the lower its quality; the smaller the tiles are in a tiling, the slower the agent arrives at its final policy but the higher its quality. Furthermore, using multiple, offset tilings can improve performance without the need for smaller tiles. The guarantees that surround common RL algorithms revolve around being able to visit every state in the environment at least once. However, many implementations of these algorithms use episode roll outs and can find themselves looping through a cycle of state-action pairs. This thesis theoretically and empirically shows that if the reward of each state-action pair in this transition cycle is identical then it is possible for the agent to temporarily diverge from learning the optimal policy. These detrimental effects of transition cycles can occur at any point of learning and, therefore, RL algorithms must heed them or risk sudden, temporary lacklustre performance. Furthermore, we consider the use of TC in conjunction with RL and find that it aggravates the detrimental effects of transition cycles to learning. This is caused by tiles inducing transition cycles. Tile Coding is still an effective and efficient method of approximation when the detrimental impacts of transition cycles are avoided. This motivates us to create a novel strategy for manual tile placement called Mixed Resolution Acyclic Tiling (MRAT). MRAT is based on heuristics derived from theoretical work and empirical studies conducted in this thesis. MRAT is empirically demonstrated to be a very effective way of improving the speed and quality of learning by using a non-uniform tile placement. MRAT is then automated and is empirically shown to outperform the state-of-the-art competitors and fixed TC. Automated MRAT (AMRAT) does not require parameter tuning and therefore has no hidden costs for its use unlike its competitors.

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Reile, Phyllis A. Barker Lewis. "Effects of D-amphetamine on choice behavior under mixed concurrent schedules." Auburn, Ala., 2007. http://repo.lib.auburn.edu/Send%2002-04-08/REILE_PHYLLIS_48.pdf.

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Abdel-Jalil, Awab. "Stimulus Control Effects of Changes in Schedules of Reinforcement." Thesis, University of North Texas, 2020. https://digital.library.unt.edu/ark:/67531/metadc1707360/.

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Sometimes, changes in consequences are accompanied by a clear stimulus change explicitly arranged by the experimenter. Other times when new consequences are in effect, there is little or no accompanying stimulus change explicitly arranged by the experimenter. These differences can be seen in the laboratory as multiple (signaled) schedules and mixed (unsignaled) schedules. The current study used college students and a single-subject design to examine the effects of introducing signaled and unsignaled schedules, and the transitions between them. In one phase, a card was flipped from purple to white every time the schedule was switched from VR-3 to FT-10. In another phase, the schedule still changed periodically, but the card always remained on the purple side. Results showed that the participants' responding was controlled by the schedule of reinforcement, by the color of the card, or both. These results suggest that changes in patterns of reinforcement lead to changes in stimulus control. In addition, the stimulus control for a behavior can come from several different sources. During teaching, it may facilitate the development of stimulus control to change the environment when a new behavior is required.

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Andrade-Plaza, Roberto. "Using Contingency Maps to Teach Requests for Information." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7259.

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Autism spectrum disorder is a developmental disorder characterized by social, behavioral, and communicative deficits. Although there is no known cure for autism, there are many research-based interventions that aid in strengthening such deficits, especially those associated with failures of stimulus control One way to address such failures is to provide additional stimuli that enhance or override information provided by naturally occurring stimuli. Contingency maps are one such example. This study uses an observing response (i.e., hand-raising) to allow the subjects to request contingency maps. The purpose of this study is to identify if contingency maps function as reinforcers and if requests for information can be acquired using an observing-response paradigm. Major findings of the present study indicate that requests for information can be acquired and maintained by access to CMs.

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Guo, Yi. "Connected and Automated Traffic Control at Signalized Intersections under Mixed-autonomy Environments." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613752599541812.

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Cherryholmes, Lauren A. "Immediate and subsequent effects of response-independent food delivery on problem behavior maintained by food." Thesis, University of North Texas, 2008. https://digital.library.unt.edu/ark:/67531/metadc6125/.

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The immediate and subsequent effects of response-independent food delivery on problem behavior maintained by food were investigated. A functional analysis indicated that the participant's problem behavior was maintained by tangible (food) reinforcement. In a subsequent analysis, each occurrence of problem behavior produced a bite of wafer in the first and third components of mixed and multiple schedules, while either response-independent food or extinction was presented in the second component. Dense and lean schedules of food delivery were assessed. Results indicated that a very dense schedule of food nearly eliminated problem behavior, a very lean schedule of food and extinction produced substantial decreases in problem behavior, and intermediate schedules did not decrease problem behavior. Response patterns were differentiated across mixed and multiple schedule arrangements, with signaled changes in the schedules (multiple schedule) generally showing more immediate and sustained effects throughout the intervention component. Implications for interpretations of the effects of the intervention are discussed.

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Weiland, Silvio, and Manfred Curbach. "Interaktion gemischter Bewehrungen bei der Verstärkung von Stahlbeton mit textilbewehrtem Beton." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2009. http://nbn-resolving.de/urn:nbn:de:bsz:14-ds-1244051366655-25294.

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Textile Bewehrungen stellen eine hervorragende Alternative zu bisherigen Verstärkungsmethoden dar. Die Wirksamkeit von Textilbetonverstärkungen konnte bereits eindrucksvoll nachgewiesen werden. Um sowohl die vorhandene Bausubstanz, als auch die Verstärkung optimal auszulasten, ist es erforderlich, das Zusammenwirken beider Bewehrungsarten unter Berücksichtigung der unterschiedlichen Verbundeigenschaften zu beschreiben. In diesem Beitrag wird das gemeinsamen Tragverhalten von Betonstahl und textiler Bewehrung eingehend erläutert. Zur Veranschaulichung wird daher vor allem die Verbundtragwirkung und deren Einfluss auf gerissene Zugglieder genauer untersucht.

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Gratclová, Kamila. "Vývoj kompozitního materiálového systému se zaměřením na matrici pro extrémní podmínky." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2016. http://www.nusl.cz/ntk/nusl-240388.

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The thesis deals with composite systems, with a focus on matrix resistant to extreme conditions. The aim of this work was to research and development matrix, resistant to high temperatures, typical in case of fire. Used theoretical knowledge were realized with subsequent laboratory research. Attention was paid matrices based binder mixed with any alkali activation of alternative raw materials and geopolymers. Scattered reinforcement featured polypropylene fibers. The subject of the practical part of the two alternatives, including a matrix based on basic ingredients - cement, alternative raw materials - high fly ash, blast furnace slag, geopolymer and polymeric components incl. combinations thereof. Laboratory research conducted by determining the fundamental material properties such as density, strengths, etc., after heat exposure. The developed materials were subjected to a temperature 1400 ° C. The conclusion was selected several recipes that were based on the resulting values found to be optimal.

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Ferroni, Nicola. "Exact Combinatorial Optimization with Graph Convolutional Neural Networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/17502/.

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Combinatorial optimization problems are typically tackled by the branch-and-bound paradigm. We propose to learn a variable selection policy for branch-and-bound in mixed-integer linear programming, by imitation learning on a diversified variant of the strong branching expert rule. We encode states as bipartite graphs and parameterize the policy as a graph convolutional neural network. Experiments on a series of synthetic problems demonstrate that our approach produces policies that can improve upon expert-designed branching rules on large problems, and generalize to instances significantly larger than seen during training.

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Weiland, Silvio. "Interaktion von Betonstahl und textiler Bewehrung bei der Biegeverstärkung mit textilbewehrtem Beton." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-37944.

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Textilbewehrter Beton zur Verstärkung von Stahlbetonbauteilen ist neben den klassischen und etablierten Verfahren eine äußerst interessante Alternative, die die Vorteile der leichten Kohlenstofffaserklebeverstärkungen mit denen von Spritzbeton mit Bewehrung verbindet. Aus den theoretischen und experimentellen Untersuchungen in dieser Arbeit können wichtige Erkenntnisse zum gemeinsamen Tragverhalten von Betonstahl und textiler Bewehrung sowie zu den Auswirkungen der verbundbedingten Unterschiede abgeleitet werden. Mit den theoretischen Betrachtungen werden das gemeinsame Tragverhalten und der Einfluss des unterschiedlichen Verbundverhaltens auf die Zugkraftaufteilung gezeigt und qualifiziert. Die Behandlung der verbundbedingten Unterschiede bei gemischt mit Betonstahl und Textil bewehrten Zuggliedern ist analog dem Vorgehen bei gemischter Beton- und Spannstahlbewehrung bzw. Klebebewehrung mit Verbundbeiwerten darstellbar. Zur Ableitung entsprechender Kennwerte werden verschiedene Möglichkeiten diskutiert. Zudem wird eine vereinfachte Bemessung vorgeschlagen. Insgesamt sind die Ergebnisse ein wesentlicher Schritt auf dem Weg zur baupraktischen Anwendung von Textilbetonverstärkungen und ermutigen bereits zum umsichtigen Einsatz unter Beachtung der Sicherheitsaspekte. Noch offene Fragen und notwendiger Klärungsbedarf sollten die Wissbegier anregen und vertiefende Forschungsvorhaben und weitere experimentelle Untersuchungen ermöglichen
Textile reinforcement represents an excellent alternative to existing techniques for strengthening of concrete structures, combining the benefits of lightweight fiber reinforced polymer strengthening with those of shotcrete with reinforcement. The theoretical and experimental studies in this thesis provide essential insights into the common load bearing behaviour of reinforcing steel and textile reinforcements as well as on the impact of the different bond characteristics of both types of rein-forcement. With the theoretical investigations, the combined load bearing behaviour and the influence of the different bond characteristics on distribution of the forces could be shown and qualified. The inter-action of both reinforcement types, taking into account the different bond characteristics, can be represented by bond coefficients analogous to the approach to mixed steel and pre-stressing-steel reinforcements. So as to derive the appropriate parameters, several options were discussed. Moreover, a simplified approach to design a TRC-strengthening-layer was proposed. Overall, the results are an essential step towards the practical application of textile reinforced con-crete for the strengthening of concrete structures and should already be encouraging the prudent use while considering the necessary safety aspects. Remaining issues and necessary clarifications should stimulate curiosity and in-depth research projects and allow further experimental studies

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Books on the topic "Mixed reinforcement"

Thal, Risa. Same ability vs. mixed-ability pair work for the development of vocabulary learning skills in the weaklearner: Do weak learners learn new vocabulary better from performing vocabulary development and reinforcement tasks in co-operative pairings with partners of the same ability than with partners of higher ability. 1997.

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Jamil, Ghazala. Media Representations. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199470655.003.0005.

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Chapter five is an attempt to further develop the discussion on discursive subalterneity of Muslims. Although media practices generally and Bollywood cinema specifically have been an arena for analysis pertaining to stereotyping of Muslims, I claim in this chapter that this analysis itself has got mired in stereotypical ways of seeing and analysing. Focusing on representation as a process of essentializing identity I connect this to Lefebvre’s ‘representation of space’ focusing on dominant discourses in news media and Bollywood cinema regarding Muslim localities. In second section of this chapter the role of news media in spawning the representation of Muslims and Muslim spaces as dens of criminal and terrorist activities. The reportage of various police action against Muslim publics and persons (such as the extra-judicial killings of terror suspects in Batla House) are discussed to discern the earlier noted trend of representation of space such that segregation is provided a discursive reinforcement.

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Book chapters on the topic "Mixed reinforcement"

Greene, Max L., Patryk Deptula, Rushikesh Kamalapurkar, and Warren E. Dixon. "Mixed Density Methods for Approximate Dynamic Programming." In Handbook of Reinforcement Learning and Control, 139–72. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-60990-0_5.

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Gatenholm, P., P. Hedenberg, and C. Klason. "Recycling of Mixed Plastics Using Cellulosic Reinforcement." In ACS Symposium Series, 367–77. Washington, DC: American Chemical Society, 1995. http://dx.doi.org/10.1021/bk-1995-0609.ch030.

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Navon, Tal, and David Peleg. "Mixed Fault Tolerance in Server Assignment: Combining Reinforcement and Backup." In Structural Information and Communication Complexity, 249–63. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01325-7_23.

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Beik Mohammadi, Hadi, Mohammad Ali Zamani, Matthias Kerzel, and Stefan Wermter. "Mixed-Reality Deep Reinforcement Learning for a Reach-to-grasp Task." In Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation, 611–23. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30487-4_47.

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Kiss, Tamás. "Assimilation and Boundary Reinforcement: Ethnic Exogamy and Socialization in Ethnically Mixed Families." In Unequal Accommodation of Minority Rights, 459–500. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78893-7_12.

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Polikutin, Aleksei, Yuri Potapov, Artem Levchenko, and Oleg Perekal’skiy. "The Stress-Strain State of Normal Sections Rubcon Bending Elements with Mixed Reinforcement." In Advances in Intelligent Systems and Computing, 586–99. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19868-8_56.

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Guo, Jingqiu, Yangzexi Liu, and Shouen Fang. "Simulated CAVs Driving and Characteristics of the Mixed Traffic Using Reinforcement Learning Method." In Smart Innovation, Systems and Technologies, 193–204. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8683-1_20.

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Bolzoni, F., G. Fumagalli, L. Lazzari, M. Ormellese, and M. P. Pedeferri. "Mixed-in inhibitors for concrete structures." In Corrosion of Reinforcement in Concrete, 185–202. Elsevier, 2007. http://dx.doi.org/10.1533/9781845692285.185.

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Ormellese, M., M. Pedeferri, G. Fumagalli, F. Bolzoni, and L. Lazzari. "Mixed-in inhibitors for concrete structures." In Corrosion of Reinforcement in Concrete. CRC Press, 2006. http://dx.doi.org/10.1201/9781439823910.ch15.

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"Materials costs – ready mixed concrete and reinforcement steel." In Spon's Asia-Pacific Construction Costs Handbook, 488. CRC Press, 2010. http://dx.doi.org/10.1201/9781482266320-50.

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Conference papers on the topic "Mixed reinforcement"

Le Tien Dung, Takashi Komeda, and Motoki Takagi. "Mixed Reinforcement Learning for Partially Observable Markov Decision Process." In 2007 International Symposium on Computational Intelligence in Robotics and Automation. IEEE, 2007. http://dx.doi.org/10.1109/cira.2007.382910.

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Bowyer, Caleb, David Greene, Tyler Ward, Marco Menendez, John Shea, and Tan Wong. "Reinforcement Learning for Mixed Cooperative/Competitive Dynamic Spectrum Access." In 2019 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN). IEEE, 2019. http://dx.doi.org/10.1109/dyspan.2019.8935725.

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Nguyen, Ngoc Duy, Saeid Nahavandi, and Thanh Nguyen. "A Human Mixed Strategy Approach to Deep Reinforcement Learning." In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, 2018. http://dx.doi.org/10.1109/smc.2018.00682.

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Ko, TsaiYen, LiWen Su, Yuchen Chang, Keigo Matsumoto, Takuji Narumi, and Michitaka Hirose. "Evaluate Optimal Redirected Walking Planning Using Reinforcement Learning." In 2020 IEEE International Symposium on Mixed and Augmented Reality Adjunct (ISMAR-Adjunct). IEEE, 2020. http://dx.doi.org/10.1109/ismar-adjunct51615.2020.00059.

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Mu, Yao, Baiyu Peng, Ziqing Gu, Shengbo Eben Li, Chang Liu, Bingbing Nie, Jianfeng Zheng, and Bo Zhang. "Mixed Reinforcement Learning for Efficient Policy Optimization in Stochastic Environments." In 2020 20th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2020. http://dx.doi.org/10.23919/iccas50221.2020.9268413.

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Li, Lei, Lei Wang, Yuanzhi Li, and Jie Sheng. "Mixed Deep Reinforcement Learning-behavior Tree for Intelligent Agents Design." In 13th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010316901130124.

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Wu, Nan, Adrien F. Vincent, and Dmitri Strukov. "Preliminary Results Towards Reinforcement Learning with Mixed-Signal Memristive Neuromorphic Circuits." In 2019 IEEE International Symposium on Circuits and Systems (ISCAS). IEEE, 2019. http://dx.doi.org/10.1109/iscas.2019.8702229.

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Vrbanic, Filip, Edouard Ivanjko, Sadko Mandzuka, and Mladen Miletic. "Reinforcement Learning Based Variable Speed Limit Control for Mixed Traffic Flows." In 2021 29th Mediterranean Conference on Control and Automation (MED). IEEE, 2021. http://dx.doi.org/10.1109/med51440.2021.9480215.

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Chu, Tianshu, and Uros Kalabic. "Model-based deep reinforcement learning for CACC in mixed-autonomy vehicle platoon." In 2019 IEEE 58th Conference on Decision and Control (CDC). IEEE, 2019. http://dx.doi.org/10.1109/cdc40024.2019.9030110.

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Luo, Jianlan, Eugen Solowjow, Chengtao Wen, Juan Aparicio Ojea, and Alice M. Agogino. "Deep Reinforcement Learning for Robotic Assembly of Mixed Deformable and Rigid Objects." In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2018. http://dx.doi.org/10.1109/iros.2018.8594353.

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