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Journal articles on the topic 'Interactive computation'

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Published: 27 February 2024

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1

Takagi, Hideyuki, and Hitoshi Iba. "Interactive evolutionary computation." New Generation Computing 23, no. 2 (June 2005): 113–14. http://dx.doi.org/10.1007/bf03037488.

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Data, Deepesh, Gowtham R. Kurri, Jithin Ravi, and Vinod M. Prabhakaran. "Interactive Secure Function Computation." IEEE Transactions on Information Theory 66, no. 9 (September 2020): 5492–521. http://dx.doi.org/10.1109/tit.2020.2980789.

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3

Kadanoff, Leo P. "Interactive Computation for Undergraduates." Physics Today 41, no. 12 (December 1988): 9–11. http://dx.doi.org/10.1063/1.2811656.

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4

Maddocks, John H., Robert S. Manning, Randy C. Paffenroth, Kathleen A. Rogers, and Jeremy A. Warner. "Interactive Computation, Parameter Continuation, and Visualization." International Journal of Bifurcation and Chaos 07, no. 08 (August 1997): 1699–715. http://dx.doi.org/10.1142/s0218127497001333.

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Nonlinear problems arising in modeling applications are frequently parameter dependent, so that families of solutions are of interest. Such problems naturally lend themselves to interactive computation that exploits parameter continuation methods combined with visualization techniques. Visualization provides both understanding of the solution set and feedback for computational steering. We describe various issues that have arisen in our investigations of problems of this general type.
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5

Parisi, Luciana. "Interactive Computation and Artificial Epistemologies." Theory, Culture & Society 38, no. 7-8 (October 19, 2021): 33–53. http://dx.doi.org/10.1177/02632764211048548.

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What is algorithmic thought? It is not possible to address this question without first reflecting on how the Universal Turing Machine transformed symbolic logic and brought to a halt the universality of mathematical formalism and the biocentric speciation of thought. The article draws on Sylvia Wynter’s discussion of the sociogenic principle to argue that both neurocognitive and formal models of automated cognition constitute the epistemological explanations of the origin of the human and of human sapience. Wynter’s argument will be related to Gilbert Simondon’s reflections on ‘technical mentality’ to consider how socio-techno-genic assemblages can challenge the biocentricism and the formalism of modern epistemology. This article turns to ludic logic as one possible example of techno-semiotic languages as a speculative overturning of sociogenic programming. Algorithmic rules become technique-signs coinciding not with classic formalism but with interactive localities without re-originating the universality of colonial and patriarchal cosmogony.
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Hannay, David G. "Interactive tools for computation theory." ACM SIGCSE Bulletin 34, no. 4 (December 2002): 68–70. http://dx.doi.org/10.1145/820127.820169.

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Skowron, Andrzej, Andrzej Jankowski, and Soma Dutta. "Interactive granular computing." Granular Computing 1, no. 2 (January 5, 2016): 95–113. http://dx.doi.org/10.1007/s41066-015-0002-1.

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Abstract Decision support in solving problems related to complex systems requires relevant computation models for the agents as well as methods for reasoning on properties of computations performed by agents. Agents are performing computations on complex objects [e.g., (behavioral) patterns, classifiers, clusters, structural objects, sets of rules, aggregation operations, (approximate) reasoning schemes]. In Granular Computing (GrC), all such constructed and/or induced objects are called granules. To model interactive computations performed by agents, crucial for the complex systems, we extend the existing GrC approach to Interactive Granular Computing (IGrC) approach by introducing complex granules (c-granules or granules, for short). Many advanced tasks, concerning complex systems, may be classified as control tasks performed by agents aiming at achieving the high-quality computational trajectories relative to the considered quality measures defined over the trajectories. Here, new challenges are to develop strategies to control, predict, and bound the behavior of the system. We propose to investigate these challenges using the IGrC framework. The reasoning, which aims at controlling of computations, to achieve the required targets, is called an adaptive judgement. This reasoning deals with granules and computations over them. Adaptive judgement is more than a mixture of reasoning based on deduction, induction and abduction. Due to the uncertainty the agents generally cannot predict exactly the results of actions (or plans). Moreover, the approximations of the complex vague concepts initiating actions (or plans) are drifting with time. Hence, adaptive strategies for evolving approximations of concepts are needed. In particular, the adaptive judgement is very much needed in the efficiency management of granular computations, carried out by agents, for risk assessment, risk treatment, and cost/benefit analysis. In the paper, we emphasize the role of the rough set-based methods in IGrC. The discussed approach is a step towards realization of the Wisdom Technology (WisTech) program, and is developed over years, based on the work experience on different real-life projects.
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Yan, Jun Rong, and Yong Min. "User Fatigue in Interactive Evolutionary Computation." Applied Mechanics and Materials 48-49 (February 2011): 1333–36. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.1333.

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User fatigue is an important issue in interactive evolutionary computation (IEC). A user’s evaluation will guide the evolution in IEC and a tired user probably misleads the algorithm. Firstly, the impact of the user fatigue is given. Secondly, the cause of the user fatigue is discussed: he/she will have to keep rational, which means that the user will have to keep the consistency between his/her evaluation and preference. And the necessity for the user to keep rational is also analyzed, which will ensure IEC to converge to the user-most-satisfactory individuals. The study of user fatigue established necessary foundation for future research.
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Kamitani, Motoki, and Tadashi Ae. "Augmented interactive evolutionary computation for composition." International Journal of Technology, Policy and Management 4, no. 4 (2004): 337. http://dx.doi.org/10.1504/ijtpm.2004.006616.

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10

Gülcü, T. C., and A. M. Barg. "Interactive function computation via polar coding." Problems of Information Transmission 52, no. 1 (January 2016): 66–91. http://dx.doi.org/10.1134/s0032946016010063.

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Madar, Janos, Janos Abonyi, and Ferenc Szeifert. "Interactive evolutionary computation in process engineering." Computers & Chemical Engineering 29, no. 7 (June 2005): 1591–97. http://dx.doi.org/10.1016/j.compchemeng.2004.12.009.

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12

Endert, Alex, Remco Chang, Chris North, and Michelle Zhou. "Semantic Interaction: Coupling Cognition and Computation through Usable Interactive Analytics." IEEE Computer Graphics and Applications 35, no. 4 (July 2015): 94–99. http://dx.doi.org/10.1109/mcg.2015.91.

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13

Selinger, Evan, and Timothy Engström. "Interactive computation is interaction with what?: A reply to Clark." Phenomenology and the Cognitive Sciences 7, no. 3 (June 26, 2008): 347–48. http://dx.doi.org/10.1007/s11097-008-9103-5.

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Yanagisawa, Hideyoshi, and Shuichi Fukuda. "Interactive Reduct Evolutional Computation for Aesthetic Design." Journal of Computing and Information Science in Engineering 5, no. 1 (March 1, 2005): 1–7. http://dx.doi.org/10.1115/1.1846055.

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We propose a method of evolving designs based on the user’s personal preferences. The method works through an interaction between the user and a computer system. The method’s objective is to help the customer to set design parameters via a simple evaluation of displayed samples. An important feature is that the design attributes to which the user pays more attention (favored features) are estimated using reducts in rough set theory and reflected when refining the design. New design candidates are generated by the user’s evaluation of design samples generated at random. The values of attributes estimated as favored features are fixed in the refined samples, while other attributes are generated at random. This interaction continues until the samples converge to a satisfactory design. In this manner, the design process efficiently evaluates personal and subjective preferences. The method is applied to design a 3D cylinder model such as a cup or vase. The method is then compared with an Interactive GA.
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15

Eskeland, Sigurd. "Non-Interactive Secure Multiparty Key Establishment." Tatra Mountains Mathematical Publications 60, no. 1 (September 1, 2014): 47–55. http://dx.doi.org/10.2478/tmmp-2014-0024.

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Abstract Cryptographic schemes that provide establishment of secret keys among a number of participants are generally known as conference key establishment schemes and key broadcasting schemes. In any case, such protocols provide secure establishment of group-oriented cryptographic keys, but with the costs of multiple transmissions of key establishment messages and in some cases multiple secret user keys. In this paper, we present a simple and straightforward efficient non-interactive group-oriented key establishment scheme that provides off-line computation of secret group keys, without computations and transmissions of key establishment messages
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16

Cabessa, Jérémie, and Hava T. Siegelmann. "The Computational Power of Interactive Recurrent Neural Networks." Neural Computation 24, no. 4 (April 2012): 996–1019. http://dx.doi.org/10.1162/neco_a_00263.

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In classical computation, rational- and real-weighted recurrent neural networks were shown to be respectively equivalent to and strictly more powerful than the standard Turing machine model. Here, we study the computational power of recurrent neural networks in a more biologically oriented computational framework, capturing the aspects of sequential interactivity and persistence of memory. In this context, we prove that so-called interactive rational- and real-weighted neural networks show the same computational powers as interactive Turing machines and interactive Turing machines with advice, respectively. A mathematical characterization of each of these computational powers is also provided. It follows from these results that interactive real-weighted neural networks can perform uncountably many more translations of information than interactive Turing machines, making them capable of super-Turing capabilities.
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17

Lee, Ciarán M., and Matty J. Hoban. "Bounds on the power of proofs and advice in general physical theories." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 472, no. 2190 (June 2016): 20160076. http://dx.doi.org/10.1098/rspa.2016.0076.

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Quantum theory presents us with the tools for computational and communication advantages over classical theory. One approach to uncovering the source of these advantages is to determine how computation and communication power vary as quantum theory is replaced by other operationally defined theories from a broad framework of such theories. Such investigations may reveal some of the key physical features required for powerful computation and communication. In this paper, we investigate how simple physical principles bound the power of two different computational paradigms which combine computation and communication in a non-trivial fashion: computation with advice and interactive proof systems. We show that the existence of non-trivial dynamics in a theory implies a bound on the power of computation with advice. Moreover, we provide an explicit example of a theory with no non-trivial dynamics in which the power of computation with advice is unbounded. Finally, we show that the power of simple interactive proof systems in theories where local measurements suffice for tomography is non-trivially bounded. This result provides a proof that Q M A is contained in P P , which does not make use of any uniquely quantum structure—such as the fact that observables correspond to self-adjoint operators—and thus may be of independent interest.
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18

Takagi, Hideyuki. "Interactive Evolutionary Computation for Analyzing Human Awareness Mechanisms." Applied Computational Intelligence and Soft Computing 2012 (2012): 1–8. http://dx.doi.org/10.1155/2012/694836.

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We discuss the importance of establishing awareness science and show the idea of using interactive evolutionary computation (IEC) as a tool for analyzing awareness mechanism and making awareness models. First, we describe the importance of human factors in computational intelligence and that IEC is one of approaches for the so-called humanized computational intelligence. Second, we show examples that IEC is used as an analysis tool for human science. As analyzing human awareness mechanism is in this kind of analyzing human characteristics and capabilities, IEC may be able to be used for this purpose. Based on this expectation, we express one idea for analyzing the awareness mechanism. This idea is to make an equivalent model of an IEC user using a learning model and find latent variables that connect inputs and outputs of the user model and that help to understand or explain the inputs-outputs relationship. Although there must be several definitions of awareness, this idea is based on one definition that awareness is to find out unknown variables that helps our understanding. If we establish a method for finding the latent variables automatically, we can realize an awareness model in computer.
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19

Takagi, Hideyuki, and Miho Ohsaki. "Interactive Evolutionary Computation-Based Hearing Aid Fitting." IEEE Transactions on Evolutionary Computation 11, no. 3 (June 2007): 414–27. http://dx.doi.org/10.1109/tevc.2006.883465.

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20

Kowaliw, Taras, Alan Dorin, and Jon McCormack. "Promoting Creative Design in Interactive Evolutionary Computation." IEEE Transactions on Evolutionary Computation 16, no. 4 (August 2012): 523–36. http://dx.doi.org/10.1109/tevc.2011.2166764.

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21

Carnahan, Brian J., Nathan Dorris, and Lois-Ann Kuntz. "Designing anthropomorphic symbols using interactive evolutionary computation." Information Design Journal 13, no. 3 (November 25, 2005): 179–90. http://dx.doi.org/10.1075/idjdd.13.3.01car.

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22

PARMEE, I. C. "Improving problem definition through interactive evolutionary computation." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 16, no. 3 (June 2002): 185–202. http://dx.doi.org/10.1017/s0890060402163050.

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Poor definition and uncertainty are primary characteristics of conceptual design processes. During the initial stages of these generally human-centric activities, little knowledge pertaining to the problem at hand may be available. The degree of problem definition will depend on information available in terms of appropriate variables, constraints, and both quantitative and qualitative objectives. Typically, the problem space develops with information gained in a dynamical process in which design optimization plays a secondary role, following the establishment of a sufficiently well-defined problem domain. This paper concentrates on background human–computer interaction relating to the machine-based generation of high-quality design information that, when presented in an appropriate manner to the designer, supports a better understanding of a problem domain. Knowledge gained from such information combined with the experiential knowledge of the designer can result in a reformulation of the problem, providing increased definition and greater confidence in the machine-based representation. Conceptual design domains related to gas turbine blade cooling systems and a preliminary air frame configuration are introduced. These are utilized to illustrate the integration of interactive evolutionary strategies that support the extraction of optimal design information, its presentation to the designer, and subsequent human-based modification of the design domain based on knowledge gained from the information received. An experimental iterative designer or evolutionary search process resulting in a better understanding of the problem and improved machine-based representation of the design domain is thus established.
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23

Kolan, Amy J. "Interactive Computation for Undergraduates: The Next Generation." Journal of Statistical Physics 167, no. 3-4 (November 9, 2016): 997–1006. http://dx.doi.org/10.1007/s10955-016-1635-4.

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24

Pei, Yan. "Principal component selection using interactive evolutionary computation." Journal of Supercomputing 73, no. 7 (August 6, 2016): 3002–20. http://dx.doi.org/10.1007/s11227-016-1829-1.

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25

O'Donnell, T. J. "Interactive computation and display of molecular surfaces." Journal of Molecular Graphics 10, no. 1 (March 1992): 39–40. http://dx.doi.org/10.1016/0263-7855(92)80016-7.

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26

Costa, Antônio Carlos da Rocha, and Graçaliz Pereira Dimuro. "Interactive Computation: Stepping Stone in the Pathway From Classical to Developmental Computation." Electronic Notes in Theoretical Computer Science 141, no. 5 (December 2005): 5–31. http://dx.doi.org/10.1016/j.entcs.2005.05.014.

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Johnson, Colin G. "Exploring Sound-Space with Interactive Genetic Algorithms." Leonardo 36, no. 1 (February 2003): 51–54. http://dx.doi.org/10.1162/002409403321152310.

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This paper describes a system that uses evolutionary computation to provide an interface to a complex sound-synthesis algorithm. The paper then considers a number of general issues to be considered when evolutionary computation is applied in artistic domains and the differences between interactive and non-interactive genetic algorithms.
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Rodis, Panteleimon. "On defining and modeling context-awareness." International Journal of Pervasive Computing and Communications 14, no. 2 (June 4, 2018): 111–23. http://dx.doi.org/10.1108/ijpcc-d-18-00003.

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Purpose This paper aims to present a methodology for defining and modeling context-awareness and describing efficiently the interactions between systems, applications and their context. Also, the relation of modern context-aware systems with distributed computation is investigated. Design/methodology/approach On this purpose, definitions of context and context-awareness are developed based on the theory of computation and especially on a computational model for interactive computation which extends the classical Turing Machine model. The computational model proposed here encloses interaction and networking capabilities for computational machines. Findings The definition of context presented here develops a mathematical framework for working with context. Also, the modeling approach of distributed computing enables us to build robust, scalable and detailed models for systems and application with context-aware capabilities. Also, it enables us to map the procedures that support context-aware operations providing detailed descriptions about the interactions of applications with their context and other external sources. Practical implications A case study of a cloud-based context-aware application is examined using the modeling methodology described in the paper so as to demonstrate the practical usage of the theoretical framework that is presented. Originality/value The originality on the framework presented here relies on the connection of context-awareness with the theory of computation and distributed computing.
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Marto, Marco, Vladimir A. Bushenkov, Keith M. Reynolds, José G. Borges, and Susete Marques. "A Web-Based Approach for Visualizing Interactive Decision Maps." Information 12, no. 1 (December 24, 2020): 9. http://dx.doi.org/10.3390/info12010009.

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This research expands the applicability of the Feasible Goals (FGoal) Pareto frontier multiple criteria method to display the Edgeworth–Pareto hull using interactive decision maps (IDMs). Emphasis is placed upon the development of a communication architecture to display the Pareto frontiers, which includes a client device, a web server, and a dedicated computation server implemented with sockets. A standalone application on the latter processes client-server requests and responses to display updated information on the client. Specifically, the dedicated computation server is responsible for calculating the information needed to generate the Edgeworth–Pareto hull. This is delivered to the web server to generate the IDM to be displayed on the client device. The key innovation of this work is a tool that is developed to aid decision-makers with a network-based computational architecture that includes a computational server constantly in communication with a web server for fast responses to client requests to represent IDMs. Results show that this innovation avoids time-consuming communication, and this approach to represent IDMs on the web facilitates collaboration among decision-makers because they can analyze several complex problems in different browser windows and decide which problem and solution better correspond to their aims.
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NAKAMURA, Tsuyoshi, Masahiro HARUTA, Yuyan Chao, Lifeng HE, and Hidenori ITOH. "Color Transfer between images using Interactive Evolutionary Computation." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 17, no. 3 (2005): 376–85. http://dx.doi.org/10.3156/jsoft.17.376.

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31

INOUE, Hiroyuki, Dan YUAN, and Kae IWATANI. "Color Combination Support Systems Using Interactive Evolutionary Computation." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 21, no. 5 (2009): 757–67. http://dx.doi.org/10.3156/jsoft.21.757.

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TAKENOUCHI, Hiroshi, and Masataka TOKUMARU. "Interactive Evolutionary Computation System with User Gaze Information." International Journal of Affective Engineering 18, no. 3 (2019): 109–16. http://dx.doi.org/10.5057/ijae.ijae-d-18-00026.

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TAKENOUCHI, Hiroshi, Masataka TOKUMARU, and Noriaki MURANAKA. "Interactive Evolutionary Computation Using a Tabu Search Algorithm." IEICE Transactions on Information and Systems E96.D, no. 3 (2013): 673–80. http://dx.doi.org/10.1587/transinf.e96.d.673.

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竹之内, 宏. "視線IEC（Interactive Evolutionary Computation with Gaze）." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 32, no. 6 (December 15, 2020): 200. http://dx.doi.org/10.3156/jsoft.32.6_200_1.

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Zhou, Lijing, Licheng Wang, Yiru Sun, and Tianyi Ai. "AntNest: Fully Non-Interactive Secure Multi-Party Computation." IEEE Access 6 (2018): 75639–49. http://dx.doi.org/10.1109/access.2018.2883775.

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36

Livadas, Panos E., John Staudhammer, and Steven Kaufmann. "Real-time interactive visibility computation for quadratic surfaces." International Journal of Computer Mathematics 31, no. 1-2 (January 1989): 19–41. http://dx.doi.org/10.1080/00207168908803785.

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Zhang, Ying, and Alice M. Agogino. "Interactive hybrid evolutionary computation for MEMS design synthesis." Mathematics and Computers in Simulation 86 (December 2012): 32–38. http://dx.doi.org/10.1016/j.matcom.2011.03.005.

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Wijns, Chris, Fabio Boschetti, and Louis Moresi. "Inverse modelling in geology by interactive evolutionary computation." Journal of Structural Geology 25, no. 10 (October 2003): 1615–21. http://dx.doi.org/10.1016/s0191-8141(03)00010-5.

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Nipkow, Tobias. "Logic and computation—Interactive proof with Cambridge LCF." Science of Computer Programming 11, no. 2 (December 1988): 178–80. http://dx.doi.org/10.1016/0167-6423(88)90007-x.

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Tang, Min, Minkyoung Lee, and Young J. Kim. "Interactive Hausdorff distance computation for general polygonal models." ACM Transactions on Graphics 28, no. 3 (July 27, 2009): 1–9. http://dx.doi.org/10.1145/1531326.1531380.

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HINSEN, KONRAD. "HIGH-LEVEL PARALLEL SOFTWARE DEVELOPMENT WITH PYTHON AND BSP." Parallel Processing Letters 13, no. 03 (September 2003): 473–84. http://dx.doi.org/10.1142/s0129626403001434.

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One of the main obstacles to a more widespread use of parallel computing in computational science is the difficulty of implementing, testing, and maintaining parallel programs. The combination of a simple parallel computation model, BSP, and a high-level programming language, Python, simplifies these tasks significantly. It allows the rapid development facilities of Python to be applied to parallel programs, providing interactive development as well as interactive debugging of parallel programs.
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Seeber, Bernhard U. "Real-time processing approaches for interactive room acoustic auralization in the rtSOFE." Journal of the Acoustical Society of America 153, no. 3_supplement (March 1, 2023): A104. http://dx.doi.org/10.1121/10.0018314.

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Room acoustic simulation of early reflections with the mirror-image method for arbitrary room geometries is an exponential problem, which, if computed to a high reflection order, will quickly exceed available computational and memory resources. The real-time Simulated Open Field Environment (rtSOFE) is freely available room-acoustic simulation and auralization software based on the mirror-image method. For auralization, rtSOFE synthesizes room impulse responses for each playback channel from the list of mirror images. A convolver program receives these seconds-long room impulse responses and convolves them for each sound source, sums across sources, and performs the playback equalization. Both programs perform computations in multiple threads in parallel using the OpenMP library. Many operations are implemented with Intel Advanced Vector Extensions (AVX) to increase processing speed. Image source trees are terminated after a definable number of invisible parent sources, keeping the number of computed mirrors manageable. With this, rtSOFE is capable of computing room impulse responses to high reflection orders in interactive real-time settings. I will present the software concept and discuss the approaches that speed up the computation.
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Hellstern, Michael, Jing Ma, Kun Yue, and Ali Shojaie. "netgsa: Fast computation and interactive visualization for topology-based pathway enrichment analysis." PLOS Computational Biology 17, no. 6 (June 11, 2021): e1008979. http://dx.doi.org/10.1371/journal.pcbi.1008979.

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Existing software tools for topology-based pathway enrichment analysis are either computationally inefficient, have undesirable statistical power, or require expert knowledge to leverage the methods’ capabilities. To address these limitations, we have overhauled NetGSA, an existing topology-based method, to provide a computationally-efficient user-friendly tool that offers interactive visualization. Pathway enrichment analysis for thousands of genes can be performed in minutes on a personal computer without sacrificing statistical power. The new software also removes the need for expert knowledge by directly curating gene-gene interaction information from multiple external databases. Lastly, by utilizing the capabilities of Cytoscape, the new software also offers interactive and intuitive network visualization.
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Kallmann, Marcelo. "Scalable Solutions for Interactive Virtual Humans That Can Manipulate Objects." Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 1, no. 1 (September 28, 2021): 69–74. http://dx.doi.org/10.1609/aiide.v1i1.18718.

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This paper presents scalable solutions for achieving virtual humans able to manipulate objects in interactive virtual environments. The scalability trades computational time with the ability of addressing increasingly difficult constraints. In time-critical environments, arm motions are computed in few milliseconds using fast analytical Inverse Kinematics. For other types of applications where collision-free motions are required, a randomized motion planner capable of generating motions of average complexity in about a second of computation time is employed. The steps required for defining and computing different types of manipulations are described in this paper.
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Cherchi, Gianmarco, Fabio Pellacini, Marco Attene, and Marco Livesu. "Interactive and Robust Mesh Booleans." ACM Transactions on Graphics 41, no. 6 (November 30, 2022): 1–14. http://dx.doi.org/10.1145/3550454.3555460.

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Boolean operations are among the most used paradigms to create and edit digital shapes. Despite being conceptually simple, the computation of mesh Booleans is notoriously challenging. Main issues come from numerical approximations that make the detection and processing of intersection points inconsistent and unreliable, exposing implementations based on floating point arithmetic to many kinds of degeneracy and failure. Numerical methods based on rational numbers or exact geometric predicates have the needed robustness guarantees, that are achieved at the cost of increased computation times that, as of today, has always restricted the use of robust mesh Booleans to offline applications. We introduce an algorithm for Boolean operations with robustness guarantees that is capable of operating at interactive frame rates on meshes with up to 200K triangles. We evaluate our tool thoroughly, considering not only interactive applications but also batch processing of large collections of meshes, processing of huge meshes containing millions of elements and variadic Booleans of hundreds of shapes altogether. In all these experiments, we consistently outperform prior robust floating point methods by at least one order of magnitude.
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Moroni, Artemis, Fernando Von Zuben, and Jônatas Manzolli. "ArTbitration: Human-Machine Interaction in Artistic Domains." Leonardo 35, no. 2 (April 2002): 185–88. http://dx.doi.org/10.1162/00240940252940568.

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In this article, the authors analyze the process of humanmachine interaction in the context of artistic domains, as a framework for exploring creativity and producing results that could not be obtained without such interaction. “ArTbitration” denotes a process aimed at improving users' aesthetic judgment involving evolutionary computation and other computational intelligence methodologies. The authors interpret it as an interactive, iterative optimization process. They also suggest ArTbitration as an effective way to produce art through the efficient manipulation of information and the proper use of computational creativity to increase the complexity of the results, without neglecting the aesthetic aspects. The article emphasizes the spoken, visual and musical domains, since these are generally characterized by the lack of a systematic way to determine the quality of the result.
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47

Alderson, David L. "Interactive Computing for Accelerated Learning in Computation and Data Science." INFORMS Transactions on Education 22, no. 2 (January 2022): 130–45. http://dx.doi.org/10.1287/ited.2021.0261.

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This article describes the motivation and design for introductory coursework in computation aimed at midcareer professionals who desire to work in data science and analytics but who have little or no background in programming. In particular, we describe how we use modern interactive computing platforms to accelerate the learning of our students both in and out of the classroom. We emphasize the importance of organizing the interaction with course material so that students learn not only to “think computationally” but also to “do computationally.” We provide details of existing courses in computation offered at the Naval Postgraduate School, and we describe their ongoing evolution in response to increased demand from members of the civilian and military workforce.
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48

Alderson, David L. "Interactive Computing for Accelerated Learning in Computation and Data Science." INFORMS Transactions on Education 22, no. 2 (January 2022): 130–45. http://dx.doi.org/10.1287/ited.2021.0261.

Full text
Abstract:
This article describes the motivation and design for introductory coursework in computation aimed at midcareer professionals who desire to work in data science and analytics but who have little or no background in programming. In particular, we describe how we use modern interactive computing platforms to accelerate the learning of our students both in and out of the classroom. We emphasize the importance of organizing the interaction with course material so that students learn not only to “think computationally” but also to “do computationally.” We provide details of existing courses in computation offered at the Naval Postgraduate School, and we describe their ongoing evolution in response to increased demand from members of the civilian and military workforce.
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49

Hao, Guo Sheng, Xiang Jun Zhao, Jia Wei Wu, and Yong Qing Huang. "Scheme of Interactive Evoking and Evolution of Creative Ideas Based on Interactive Evolutionary Computation." Applied Mechanics and Materials 48-49 (February 2011): 1006–9. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.1006.

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Creative ideas are important not only for an enterprise but also for a country. The scheme for computer to produce creative ideas is given. There are two parts in the scheme. The first part is for computer to realize the creation skills, which will bring thousands or millions of candidate ideas. The second part is to optimize the candidate ideas with interactive evolutionary computation (IEC). When the sentences that IEC optimized are submitted to the user, his/her thought would be invoked, and new ideas would come to his/her brain. This scheme supports a new way for computer to help user produce creative ideas.
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50

FUJISAKI, Minatsu, Hiroshi TAKENOUCHI, and Masataka TOKUMARU. "Interactive Evolutionary Computation System Using Multiple Users’ Gaze Information." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 30, no. 4 (August 15, 2018): 613–22. http://dx.doi.org/10.3156/jsoft.30.4_613.

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