Academic literature on the topic 'Actor'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Actor.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Actor"
Nenonen, Suvi, and Kaj Storbacka. "Actors, Actor Engagement and Value Creation." Journal of Creating Value 4, no. 2 (November 2018): 196–98. http://dx.doi.org/10.1177/2394964318809172.
Full textBarclay, Kari. "Willful Actors: Valuing Resistance in American Actor Training." Journal of Dramatic Theory and Criticism 34, no. 1 (2019): 123–41. http://dx.doi.org/10.1353/dtc.2019.0027.
Full textMunteanu, Radu, and Marin Apetroae. "Journal relatedness: An actor-actor and actor-objectives case study." Scientometrics 73, no. 2 (August 3, 2007): 215–30. http://dx.doi.org/10.1007/s11192-007-1735-7.
Full textJobbagy, Zoltan, Goran Boros, and Levente Sandor Kovats. "Some Remarks on the Dynamics of Strong Actor / Weak Actor Interaction." Land Forces Academy Review 26, no. 2 (June 1, 2021): 108–17. http://dx.doi.org/10.2478/raft-2021-0016.
Full textLi, Loic Pengtao, Biljana Juric, and Roderick J. Brodie. "Actor engagement valence." Journal of Service Management 29, no. 3 (May 4, 2018): 491–516. http://dx.doi.org/10.1108/josm-08-2016-0235.
Full textGrehan, Helena. "Actors, Spectators, and “Vibrant” Objects: Kris Verdonck’s ACTOR #1." TDR/The Drama Review 59, no. 3 (September 2015): 132–39. http://dx.doi.org/10.1162/dram_a_00475.
Full textHerrera, Brian Eugenio. "My Actor Alibi." Theatre Survey 57, no. 3 (August 10, 2016): 409–11. http://dx.doi.org/10.1017/s0040557416000417.
Full textMcNeill, David. "Speech-gesture mimicry in performance: an actor → audience, author → actor, audience → actor triangle." Journal for Cultural Research 19, no. 1 (July 2014): 15–29. http://dx.doi.org/10.1080/14797585.2014.920184.
Full textGarritz, Andoni. "¿Quién es el primer actor en el acto educativo?" Educación Química 1, no. 3 (August 31, 2018): 102. http://dx.doi.org/10.22201/fq.18708404e.1990.3.66997.
Full textRajaravivarma, K. R., and Suresh Chandra Das. "THERUKUTHU AS A TRAINING METHOD FOR CONTEMPORARY THEATRE ACTOR." ShodhKosh: Journal of Visual and Performing Arts 3, no. 2 (July 30, 2022): 115–22. http://dx.doi.org/10.29121/shodhkosh.v3.i2.2022.147.
Full textDissertations / Theses on the topic "Actor"
Kilarski, Sharon K. "An emerging theory of actor learning : the actors' perspective /." free to MU campus, to others for purchase, 2000. http://wwwlib.umi.com/cr/mo/fullcit?p9988676.
Full textKrishnakumar, Sita Srinivasaraghavan. "Intelligent actor mobility in wireless sensor and actor networks." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24735.
Full textCommittee Chair: Abler, Randal T.; Committee Member: Copeland, John A.; Committee Member: Haas, Kevin; Committee Member: Moore II, Elliot; Committee Member: Owen III, Henry L.
Mahjoub, Reem Khalid. "Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks." Thesis, University of Bridgeport, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10745143.
Full textWireless sensor networks (WSNs) are becoming widely used worldwide. Wireless Sensor and Actor Networks (WSANs) represent a special category of WSNs wherein actors and sensors collaborate to perform specific tasks. WSANs have become one of the most preeminent emerging type of WSNs. Sensors with nodes having limited power resources are responsible for sensing and transmitting events to actor nodes. Actors are high-performance nodes equipped with rich resources that have the ability to collect, process, transmit data and perform various actions. WSANs have a unique architecture that distinguishes them from WSNs. Due to the characteristics of WSANs, numerous challenges arise. Determining the importance of factors usually depends on the application requirements.
The actor nodes are the spine of WSANs that collaborate to perform the specific tasks in an unsubstantiated and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power fatigue of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. It is essential to keep inter-actor connectivity in order to insure network connectivity. Thus, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). For network recovery process from actor node failure, optimal re-localization and coordination techniques should take place.
In this work, we propose an efficient actor recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balances the network performance. The packet is handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets (Either from actor or sensor). This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, we compare the performance of our proposed work with state-of the art localization algorithms. Our experimental results show superior performance in regards to network life, residual energy, reliability, sensor/ actor recovery time and data recovery.
Helmhout, Jan Martin. "The social cognitive actor a multi-actor simulation of organisations /." [S.l. : [Groningen : s.n.] ; University Library Groningen] [Host], 2006. http://irs.ub.rug.nl/ppn/297984268.
Full textPippen, Judith Irene. "Inscribing actors' bodies : towards an epistemology of movement praxis in actor training." Thesis, Queensland University of Technology, 1998.
Find full textKonda, Vijaymohan (Vijaymohan Gao) 1973. "Actor-critic algorithms." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/8120.
Full textIncludes bibliographical references (leaves 143-147).
Many complex decision making problems like scheduling in manufacturing systems, portfolio management in finance, admission control in communication networks etc., with clear and precise objectives, can be formulated as stochastic dynamic programming problems in which the objective of decision making is to maximize a single "overall" reward. In these formulations, finding an optimal decision policy involves computing a certain "value function" which assigns to each state the optimal reward one would obtain if the system was started from that state. This function then naturally prescribes the optimal policy, which is to take decisions that drive the system to states with maximum value. For many practical problems, the computation of the exact value function is intractable, analytically and numerically, due to the enormous size of the state space. Therefore one has to resort to one of the following approximation methods to find a good sub-optimal policy: (1) Approximate the value function. (2) Restrict the search for a good policy to a smaller family of policies. In this thesis, we propose and study actor-critic algorithms which combine the above two approaches with simulation to find the best policy among a parameterized class of policies. Actor-critic algorithms have two learning units: an actor and a critic. An actor is a decision maker with a tunable parameter. A critic is a function approximator. The critic tries to approximate the value function of the policy used by the actor, and the actor in turn tries to improve its policy based on the current approximation provided by the critic. Furthermore, the critic evolves on a faster time-scale than the actor.
(cont.) We propose several variants of actor-critic algorithms. In all the variants, the critic uses Temporal Difference (TD) learning with linear function approximation. Some of the variants are inspired by a new geometric interpretation of the formula for the gradient of the overall reward with respect to the actor parameters. This interpretation suggests a natural set of basis functions for the critic, determined by the family of policies parameterized by the actor's parameters. We concentrate on the average expected reward criterion but we also show how the algorithms can be modified for other objective criteria. We prove convergence of the algorithms for problems with general (finite, countable, or continuous) state and decision spaces. To compute the rate of convergence (ROC) of our algorithms, we develop a general theory of the ROC of two-time-scale algorithms and we apply it to study our algorithms. In the process, we study the ROC of TD learning and compare it with related methods such as Least Squares TD (LSTD). We study the effect of the basis functions used for linear function approximation on the ROC of TD. We also show that the ROC of actor-critic algorithms does not depend on the actual basis functions used in the critic but depends only on the subspace spanned by them and study this dependence. Finally, we compare the performance of our algorithms with other algorithms that optimize over a parameterized family of policies. We show that when only the "natural" basis functions are used for the critic, the rate of convergence of the actor- critic algorithms is the same as that of certain stochastic gradient descent algorithms ...
by Vijaymohan Konda.
Ph.D.
Hildebrand, Sara. "Creating an actor." Thesis, University of Iowa, 2015. https://ir.uiowa.edu/etd/1628.
Full textScafuto, Vincenzo. "Actor Kit: Design and Development of an Actor Framework for Swift." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2016.
Find full textThimmapuram, Aravind. "Distributed recovery of actor failures in wireless sensor and actor networks /." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1559859581&sid=7&Fmt=2&clientId=1509&RQT=309&VName=PQD.
Full textGuneydas, Ismail. "ACTOR POSITIONING IN WIRELESS SENSOR AND ACTOR NETWORKS USING MATCHING THEORY." Available to subscribers only, 2008. http://proquest.umi.com/pqdweb?did=1674095431&sid=1&Fmt=2&clientId=1509&RQT=309&VName=PQD.
Full text"Department of Computer Science." Keywords: Gale-Shapley, Wireless sensor networks. Includes bibliographical references (p. 42-45). Also available online.
Books on the topic "Actor"
Fundação Calouste Gulbenkian. Serviço de Belas-Artes., ed. Ciclo de cinema actor/actor. [Lisbon: s.n., 1987.
Find full textSomervill, Barbara A. Actor. Ann Arbor, Mich: Cherry Lake Pub., 2012.
Find full textActor. México, D.F: La Cabra Ediciones, 2009.
Find full textActor. Ann Arbor, Mich: Cherry Lake Pub., 2012.
Find full textActor. [Place of publication not identified]: iUniverse Com, 2013.
Find full textHall, Parnell. Actor. New York: Mysterious Press, 1993.
Find full textQuinlan, Kathryn A. Actor. Mankato, Minn: Capstone High/Low Books, 1998.
Find full textStroppel, Frederick. Actor! New York: Samuel French, 2003.
Find full textThe actor. New York: Doubleday, 1987.
Find full text1959-, Hodge Alison, ed. Actor training. 2nd ed. New York, NY: Routledge, 2010.
Find full textBook chapters on the topic "Actor"
Weik, Martin H. "actor." In Computer Science and Communications Dictionary, 22. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_274.
Full textKautsch, Andrés Ibañez. "The Main Actor & Final Actors." In Modern Concurrency on Apple Platforms, 151–65. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8695-1_8.
Full textde Vries, Henk J. "Actor Needs." In Standardization: A Business Approach to the Role of National Standardization Organizations, 55–72. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-3042-5_4.
Full textSummers, Alexander J., and Peter Müller. "Actor Services." In Programming Languages and Systems, 699–726. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49498-1_27.
Full textAulin, Arvid. "Human Actor." In The Origins of Economic Growth, 155–67. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60712-7_10.
Full textWalsh, Keri. "Method Actor." In Mickey Rourke, 10–31. London: British Film Institute, 2014. http://dx.doi.org/10.1007/978-1-84457-925-9_2.
Full textMartínez-Ariño, Julia. "Actor constellations." In Urban Secularism, 38–56. Abingdon, Oxon ; New York, NY, USA : Routledge, 2021. | Series: Routledge advances in sociology: Routledge, 2020. http://dx.doi.org/10.4324/9780429320606-3.
Full textAnderson, Joel. "Actor portraits." In Theatre & Photography, 39–45. London: Macmillan Education UK, 2015. http://dx.doi.org/10.1007/978-1-137-34562-2_6.
Full textHartley, Dean S. "Actor Ontology." In Understanding Complex Systems, 75–88. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-75337-9_3.
Full textDe Gruyter, Chris. "Actor Perspectives." In Travel Plans for New Residential Developments: Insights from Theory and Practice, 83–100. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-2092-6_6.
Full textConference papers on the topic "Actor"
Koc, Ozcan, Chaiporn Jaikaeo, and Chien-Chung Shen. "Navigating actors in mobile sensor actor networks." In the Ffrst ACM workshop. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1287731.1287736.
Full textCedersjo, Gustav, and Jorn W. Janneck. "Actor classification using actor machines." In 2013 Asilomar Conference on Signals, Systems and Computers. IEEE, 2013. http://dx.doi.org/10.1109/acssc.2013.6810612.
Full textZamanifar, Azadeh, Mohsen Sharifi, and Omid Kashefi. "Self Actor-Actor Connectivity Restoration in Wireless Sensor and Actor Networks." In 2009 First Asian Conference on Intelligent Information and Database Systems, ACIIDS. IEEE, 2009. http://dx.doi.org/10.1109/aciids.2009.45.
Full textDima, Sofia-Maria, John Gialelis, and Stavros Koubias. "Knowledge based actor to actor coordination in Wireless Sensor and Actor Networks." In Factory Automation (ETFA 2011). IEEE, 2011. http://dx.doi.org/10.1109/etfa.2011.6059187.
Full textChinnappen-Rimer, S., and G. P. Hancke. "Actor Coordination in Wireless Sensor-Actor Networks." In 2009 Annual IEEE India Conference. IEEE, 2009. http://dx.doi.org/10.1109/indcon.2009.5409466.
Full textAlaiwy, Mona H., Fatema H. Alaiwy, and Sami Habib. "Optimization of Actors Placement within Wireless Sensor-Actor Networks." In 2007 IEEE Symposium on Computers and Communications. IEEE, 2007. http://dx.doi.org/10.1109/iscc.2007.4381511.
Full textLamghari, Soufiane, Guillaume-Alexandre Bilodeau, and Nicolas Saunier. "ActAR: Actor-Driven Pose Embeddings for Video Action Recognition." In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2022. http://dx.doi.org/10.1109/cvprw56347.2022.00055.
Full textHabib, Sami J., M. Safar, and N. El-Sayed. "Automatic Placement of Actors within Wireless Sensor-Actor Networks." In 2008 Australasian Telecommunication Networks and Applications Conference (ATNAC). IEEE, 2008. http://dx.doi.org/10.1109/atnac.2008.4783327.
Full textKamali, Maryam, Saeed Sedighian, and Mohsen Sharifi. "A distributed recovery mechanism for actor-actor connectivity in wireless sensor actor networks." In 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). IEEE, 2008. http://dx.doi.org/10.1109/issnip.2008.4761984.
Full textLeite, Luís, and Veronica Orvalho. "Anim-actor." In the 8th International Conference. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/2071423.2071505.
Full textReports on the topic "Actor"
Hewitt, Carl. The Actor Model. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada260196.
Full textBenson, Dennis, Jay Mead, William Walker, and Douglas Blazer. Air Force Bad Actor Program. Fort Belvoir, VA: Defense Technical Information Center, February 1997. http://dx.doi.org/10.21236/ada326050.
Full textArango Dávila, Lina María, and Jonathan Röders. Decentralised and Community-Driven Formerly Armed Actor Reintegration. Trust After Betrayal Research Brief Series, May 2024. http://dx.doi.org/10.59498/70347.
Full textGill, Paul. The Data Collection Challenge: Experiences Studying Lone-actor Terrorism. RESOLVE Network, February 2020. http://dx.doi.org/10.37805/rve2020.2.
Full textGreen, Carla. An attempt to reduce actor-observer differences in attributions. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.5589.
Full textMoss, J. C. Elegant Coercion and Iran: Beyond the Unitary Actor Model. Fort Belvoir, VA: Defense Technical Information Center, May 2005. http://dx.doi.org/10.21236/ada476960.
Full textRöders, Jonathan, and Mari Mirasol. Research Brief: Deconstructing the Formerly Armed Actor Threat Stigma. Trust After Betrayal, January 2023. http://dx.doi.org/10.59498/68050.
Full textPrudnikov, Andrei, and Julia Lektorova. Image of the Political Actor. Overview of Current Practices. DOI CODE, 2022. http://dx.doi.org/10.18411/doicode-2023.249.
Full textMcFee, Erin, and Connor Christensen. Formerly Armed Actor Reintegration: A Crucial Pillar of International Security. Trust After Betrayal, January 2024. http://dx.doi.org/10.59498/13285.
Full textMagyar, Luke, and Jonathan Röders. Implications of Armed Group Hierarchies for Formerly Armed Actor Reintegration. Trust After Betrayal Research Brief Series, April 2024. http://dx.doi.org/10.59498/18037.
Full text