Artículos de revistas: "Ant"

1

Beischer, Thomas G. "Ant Farm 1968-1978 Ant Farm." Journal of the Society of Architectural Historians 64, no. 3 (September 2005): 367–69. http://dx.doi.org/10.2307/25068171.

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2

Popp, Michael P., Reinhard Grisshammer, Paul A. Hargrave, and W. Clay Smith. "Ant opsins: Sequences from the Saharan silver ant and the carpenter ant." Invertebrate Neuroscience 1, no. 4 (March 1996): 323–29. http://dx.doi.org/10.1007/bf02211912.

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3

Milius, Susan. "Ant Enforcers." Science News 162, no. 10 (September 7, 2002): 147. http://dx.doi.org/10.2307/4013760.

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4

Saco, Santiago. "ANT Presentación." El Antoniano 135, no. 1 (January 10, 2022): 1–2. http://dx.doi.org/10.51343/anto.v135i1.855.

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en Wuhan, China, denominado inicialmente como el Virus de Wuhan, el cual es n noviembre del 2019, se anunció el descubrimiento de un nuevo virus detectado producido por un coronavirus, llamado así por tener picos o espigas en forma de corona.  Luego la Organización Mundial de la Salud presento la alarma y el 11 de marzo del 2020 lo reconoció como una pandemia producida por el SARS-CoV-2, recomendando una serie de medidas de prevención para evitar su difusión. En muy poco tiempo el virus se fue difundiendo a todos los continentes: Asia, Oceanía, Europa, y América, en marzo del 2020 ya había llegado al Perú a través de un peruano que había pasado sus vacaciones en varios países europeos. Inmediatamente de reportado el primer caso, el gobierno del Perú tomo una serie de medidas sanitarias a nivel nacional para evitar su difusión, como la cuarentena, el distanciamiento social, el uso de mascarillas, el lavado frecuente de manos, suspensión de las clases presenciales escolares y universitarias, suspensión de los vuelos, cierre de fronteras, entre otras actividades. En el Cusco se tomaron las mismas medidas, confinándonos en nuestras casas por largos meses. Los primeros casos que se presentaron en Cusco fueron importados por turistas extranjeros

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5

Johnson, Christine A., and Joan M. Herbers. "ANT PARASITISM." Bulletin of the Ecological Society of America 87, no. 1 (January 2006): 19. http://dx.doi.org/10.1890/0012-9623(2006)87[19:ap]2.0.co;2.

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6

Nanda, Bijaya Kumar, and Satchidananda Dehuri. "Ant Miner." International Journal of Applied Evolutionary Computation 11, no. 2 (April 2020): 47–64. http://dx.doi.org/10.4018/ijaec.2020040104.

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Discovering classification rules from large data is an important task of data mining and is gaining considerable attention. This article presents a novel ant miner for classification rule mining. Our ant miner is inspired by research on the behavior of real ant colonies, simulated annealing, and some data mining concepts as well as principles. Here we present a Michigan style approach for single objective classification rule mining. The algorithm is tested on a few benchmark datasets drawn from UCI repository. Our experimental outcomes confirm that ant miner-HMC (Hybrid Michigan Style Classification) is significantly better than ant-miner-MC (Michigan Style Classification).

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7

Nanda, Bijaya Kumar, and Satchidananda Dehuri. "Ant Miner." International Journal of Artificial Intelligence and Machine Learning 10, no. 1 (January 2020): 45–59. http://dx.doi.org/10.4018/ijaiml.2020010104.

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In data mining the task of extracting classification rules from large data is an important task and is gaining considerable attention. This article presents a novel ant miner for classification rule mining. The ant miner is inspired by researches on the behaviour of real ant colonies, simulated annealing, and some data mining concepts as well as principles. This paper presents a Pittsburgh style approach for single objective classification rule mining. The algorithm is tested on a few benchmark datasets drawn from UCI repository. The experimental outcomes confirm that ant miner-HPB (Hybrid Pittsburgh Style Classification) is significantly better than ant-miner-PB (Pittsburgh Style Classification).

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8

Mirsky, Steve. "Ant Thesis." Scientific American 289, no. 1 (July 2003): 27. http://dx.doi.org/10.1038/scientificamerican0703-27c.

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9

Hoffman, Donald R. "Ant venoms." Current Opinion in Allergy and Clinical Immunology 10, no. 4 (August 2010): 342–46. http://dx.doi.org/10.1097/aci.0b013e328339f325.

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10

Fessenden, Marissa. "Ant Invasion!" Scientific American 308, no. 5 (April 16, 2013): 20. http://dx.doi.org/10.1038/scientificamerican0513-20.

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11

Broadway, George. "Ant Lions." Castlemaine Naturalist 47, no. 508 (May 2022): 9. http://dx.doi.org/10.5962/p.402258.

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12

Ross, K. G. "Ant Invaders." Science 265, no. 5179 (September 16, 1994): 1744–45. http://dx.doi.org/10.1126/science.265.5179.1744.

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13

Dorigo, Marco, Gianni Di Caro, and Thomas Stützle. "Ant algorithms." Future Generation Computer Systems 16, no. 8 (June 2000): v—vii. http://dx.doi.org/10.1016/s0167-739x(00)00041-8.

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14

Stützle, Thomas, and Holger H. Hoos. "– Ant System." Future Generation Computer Systems 16, no. 8 (June 2000): 889–914. http://dx.doi.org/10.1016/s0167-739x(00)00043-1.

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15

Pérez-Espona, Sílvia. "Ant Ecology." Animal Behaviour 80, no. 2 (August 2010): 347. http://dx.doi.org/10.1016/j.anbehav.2010.05.016.

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16

Jansen, Till. "Beyond ANT." European Journal of Social Theory 20, no. 2 (May 3, 2016): 199–215. http://dx.doi.org/10.1177/1368431016646506.

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Actor-Network-Theory (ANT) offers an ‘infra-language’ of the social that allows one to trace social relations very dynamically, while at the same time dissolving human agency, thus providing a flat and de-centred way into sociology. However, ANT struggles with its theoretical design that may lead us to reduce agency to causation and to conceptualize actor-networks as homogeneous ontologies of force. This article proposes to regard ANT’s inability to conceptualize reflexivity and the interrelatedness of different ontologies as the fundamental problem of the theory. Drawing on Günther, it offers an ‘infra-language’ of reflexive relations while maintaining ANT’s de-centred approach. This would enable us to conceptualize actor-networks as non-homogeneous, dynamic and connecting different societal rationales while maintaining the main strengths of ANT.

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17

K, Jillian. "Ant-agonism." Scientific American 322, no. 5 (May 2020): 16. http://dx.doi.org/10.1038/scientificamerican0520-16b.

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18

White, Gwenda. "Ant-Plants." Metamorphosis Australia : magazine of the Butterfly & Other Invertebrates Club 74 (September 2014): 9–10. https://doi.org/10.5962/p.420002.

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19

Gotelli, Nicholas J. "Ant Community Structure: Effects of Predatory Ant Lions." Ecology 77, no. 2 (March 1996): 630–38. http://dx.doi.org/10.2307/2265636.

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20

Padje, Anouk van ’t, Lennart J. J. van de Peppel, and Duur K. Aanen. "Evolution: Ant trail pheromones promote ant–aphid mutualisms." Current Biology 31, no. 21 (November 2021): R1437—R1439. http://dx.doi.org/10.1016/j.cub.2021.09.046.

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21

Greenfield, Gary, and Penousal Machado. "Ant- and Ant-Colony-Inspired ALife Visual Art." Artificial Life 21, no. 3 (August 2015): 293–306. http://dx.doi.org/10.1162/artl_a_00170.

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Ant- and ant-colony-inspired ALife art is characterized by the artistic exploration of the emerging collective behavior of computational agents, developed using ants as a metaphor. We present a chronology that documents the emergence and history of such visual art, contextualize ant- and ant-colony-inspired art within generative art practices, and consider how it relates to other ALife art. We survey many of the algorithms that artists have used in this genre, address some of their aims, and explore the relationships between ant- and ant-colony-inspired art and research on ant and ant colony behavior.

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22

Diaf, Moussa, Kamal Hammouche, and Patrick Siarry. "From the Real Ant to the Artificial Ant." International Journal of Signs and Semiotic Systems 2, no. 2 (July 2012): 45–68. http://dx.doi.org/10.4018/ijsss.2012070103.

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Biological studies highlighting the collective behavior of ants in fulfilling various tasks by using their complex indirect communication process have constituted the starting point for many physical systems and various ant colony algorithms. Each ant colony is considered as a superorganism which operates as a unified entity made up of simple agents. These agents (ants) interact locally with one another and with their environment, particularly in finding the shortest path from the nest to food sources without any centralized control dictating the behavior of individual agents. It is this coordination mechanism that has inspired researchers to develop plenty of metaheuristic algorithms in order to find good solutions for NP-hard combinatorial optimization problems. In this article, the authors give a biological description of these fascinating insects and their complex indirect communication process. From this rich source of inspiration for researchers, the authors show how, through the real ant, artificial ant is modeled and applied in combinatorial optimization, data clustering, collective robotics, and image processing.

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23

Orivel, Jérôme, Christine Errard, and A. Dejean. "Ant gardens: interspecific recognition in parabiotic ant species." Behavioral Ecology and Sociobiology 40, no. 2 (February 20, 1997): 87–93. http://dx.doi.org/10.1007/s002650050319.

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24

AMADOR-VARGAS, SABRINA, JUAN ANDRÉS MARTÍNEZ, PAOLA GIRALDO-BELTRÁN, ROSA MARÍA GONZÁLEZ, SETH RIFKIN, and VICTOR GAMARRA-TOLEDO. "Ant body posture: gaster curling increases ant speed." Ecological Entomology 36, no. 5 (September 13, 2011): 663–66. http://dx.doi.org/10.1111/j.1365-2311.2011.01311.x.

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25

Boardman, Charles R., and Amnon Sonnenberg. "Upping the “ant-e” on endoscopic ant sightings." Gastrointestinal Endoscopy 70, no. 6 (December 2009): 1245–46. http://dx.doi.org/10.1016/j.gie.2009.07.015.

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26

Turner, Peter. "Observations: Blue Ant (or Bluebottle ant) Diamma bicolor." Castlemaine Naturalist 49-11, no. 537 (2024): 12. https://doi.org/10.5962/p.413372.

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27

Ness, J. H., J. L. Bronstein, A. N. Andersen, and J. N. Holland. "ANT BODY SIZE PREDICTS DISPERSAL DISTANCE OF ANT-ADAPTED SEEDS: IMPLICATIONS OF SMALL-ANT INVASIONS." Ecology 85, no. 5 (May 2004): 1244–50. http://dx.doi.org/10.1890/03-0364.

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28

Sanders, Nathan J., Gregory M. Crutsinger, Robert R. Dunn, Jonathan D. Majer, and Jacques H. C. Delabie. "An Ant Mosaic Revisited: Dominant Ant Species Disassemble Arboreal Ant Communities but Co-Occur Randomly." Biotropica 39, no. 3 (May 2007): 422–27. http://dx.doi.org/10.1111/j.1744-7429.2007.00263.x.

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29

LeBrun, Edward G., John Abbott, and Lawrence E. Gilbert. "Imported crazy ant displaces imported fire ant, reduces and homogenizes grassland ant and arthropod assemblages." Biological Invasions 15, no. 11 (April 21, 2013): 2429–42. http://dx.doi.org/10.1007/s10530-013-0463-6.

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30

Volp, Trevor M., and Lori Lach. "An Epiphytic Ant-Plant Mutualism Structures Arboreal Ant Communities." Environmental Entomology 48, no. 5 (July 15, 2019): 1056–62. http://dx.doi.org/10.1093/ee/nvz083.

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Abstract Arboreal ant communities are primarily structured by interactions among ant species, food availability, and physical structures within the environment. Epiphytes are a common feature of tropical forests that can provide ants with both food and nesting space. To date, little work has examined what role epiphytic ant-plants play in structuring arboreal ant communities. We surveyed ant species inhabiting the Australian epiphytic ant-plant Myrmecodia beccarii Hook.f. (Gentianales: Rubiaceae) and how arboreal ant communities are structured in relation to M. beccarii presence on trees. Myrmecodia beccarii was inhabited by the ant Philidris cordata Smith, F. (Hymenoptera: Formicidae) on the majority of Melaleuca viridiflora Sol. Ex Gaertn. (Myrtales: Myrtaceae) trees with ant-occupied ant-plants at our two sites. Dominant arboreal ant species at both study sites exhibited discrete, nonoverlapping distributions, and C-score analysis detected an ant mosaic at one site. The distribution of P. cordata was limited by the distribution of ant-plants for both sites. Philidris cordata dominance on trees was also determined by the presence of M. beccarii occupied by P. cordata at both sites. We suggest that by providing P. cordata with nesting space M. beccarii plays a role in structuring these arboreal ant communities.

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31

Doerr, Benjamin, Frank Neumann, Dirk Sudholt, and Carsten Witt. "Runtime analysis of the 1-ANT ant colony optimizer." Theoretical Computer Science 412, no. 17 (April 2011): 1629–44. http://dx.doi.org/10.1016/j.tcs.2010.12.030.

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32

Mayang, Ajeng, and Savitri Galih. "Comparative Performance AODV-ANT and AOMDV-ANT in BlackHole." International Journal of Engineering & Technology 7, no. 4.34 (December 13, 2018): 358. http://dx.doi.org/10.14419/ijet.v7i4.34.25780.

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In this paper, we simulate the black hole attack to compare performance AODV-ANT and AOMDV-ANT to support the advance of the node communications to deliver a good management. In our simulation, the result shows AODV-ANT has decrease packets receive in Blackhole attack comparing without black hole until 0.03%, and while in AOMDV-ANT decrease until 0.47%. But, in throughput, AOMDV-ANT is better than AODV-ANT. The result is AOMDV-ANT has decrease throughput in Blackhole attack comparing without black hole until 0.93%, and while in AODV-ANT decrease until 1.85%. Then, in packet delivery ratio (PDR), AODV-ANT has decrease PDR in Blackhole attack comparing without black hole until 10.357%, and while in AOMDV-ANT decrease until 13.57%. In simulation performed, the impact of the black hole can be seen in the PDR. This occurs because of the random node mobility. For our simulations using NS-2:35 as a tool.

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33

HASEGAWA, Hiroshi, and Sou OKIYAMA. "Improvement of Ant Mill in Ant Colony Topology Optimization." Proceedings of Mechanical Engineering Congress, Japan 2023 (2023): J122p—05. http://dx.doi.org/10.1299/jsmemecj.2023.j122p-05.

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34

Hama Rashid, Deeam Najmadeen, Tarik A. Rashid, and Seyedali Mirjalili. "ANA: Ant Nesting Algorithm for Optimizing Real-World Problems." Mathematics 9, no. 23 (December 2, 2021): 3111. http://dx.doi.org/10.3390/math9233111.

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In this paper, a novel swarm intelligent algorithm is proposed called ant nesting algorithm (ANA). The algorithm is inspired by Leptothorax ants and mimics the behavior of ants searching for positions to deposit grains while building a new nest. Although the algorithm is inspired by the swarming behavior of ants, it does not have any algorithmic similarity with the ant colony optimization (ACO) algorithm. It is worth mentioning that ANA is considered a continuous algorithm that updates the search agent position by adding the rate of change (e.g., step or velocity). ANA computes the rate of change differently as it uses previous, current solutions, fitness values during the optimization process to generate weights by utilizing the Pythagorean theorem. These weights drive the search agents during the exploration and exploitation phases. The ANA algorithm is benchmarked on 26 well-known test functions, and the results are verified by a comparative study with genetic algorithm (GA), particle swarm optimization (PSO), dragonfly algorithm (DA), five modified versions of PSO, whale optimization algorithm (WOA), salp swarm algorithm (SSA), and fitness dependent optimizer (FDO). ANA outperformances these prominent metaheuristic algorithms on several test cases and provides quite competitive results. Finally, the algorithm is employed for optimizing two well-known real-world engineering problems: antenna array design and frequency-modulated synthesis. The results on the engineering case studies demonstrate the proposed algorithm’s capability in optimizing real-world problems.

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35

Keeler, Kathleen H. "Ant-Plant Interactions." Ecology 68, no. 1 (February 1987): 235–36. http://dx.doi.org/10.2307/1938832.

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36

Latour, Bruno. "On Recalling ANT." Philosophical Literary Journal Logos 27, no. 1 (2017): 201–14. http://dx.doi.org/10.22394/0869-5377-2017-1-201-214.

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37

Paganelli, Leonardo. "Soph. "Ant." 514." Quaderni Urbinati di Cultura Classica 24, no. 3 (1986): 133. http://dx.doi.org/10.2307/20538951.

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38

Mori, Scott A., Camilla R. Huxley, and David F. Cutler. "Ant-Plant Interactions." Brittonia 44, no. 3 (July 1992): 385. http://dx.doi.org/10.2307/2806946.

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39

Ammon, Sabine. "ANT im Architekturbüro." Zeitschrift für Ästhetik und Allgemeine Kunstwissenschaft 57, no. 1 (2012): 128–50. http://dx.doi.org/10.28937/1000106207.

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40

Matsushita, Takahiko. "Ant Venom Glycopeptide." Trends in Glycoscience and Glycotechnology 34, no. 201 (September 25, 2022): E99—E100. http://dx.doi.org/10.4052/tigg.2217.6e.

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41

Matsushita, Takahiko. "Ant Venom Glycopeptide." Trends in Glycoscience and Glycotechnology 34, no. 201 (September 25, 2022): J99. http://dx.doi.org/10.4052/tigg.2217.6j.

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42

Milius, Susan. "Ant Traffic Flow." Science News 162, no. 25/26 (December 21, 2002): 388. http://dx.doi.org/10.2307/4013963.

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43

Williams, David F., and Sanford D. Porter. "Fire Ant Control." Science 264, no. 5166 (June 17, 1994): 1653. http://dx.doi.org/10.1126/science.264.5166.1653.a.

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44

Lindemann, Anna. ""Ant Queen Aria"." Women and Music: A Journal of Gender and Culture 25, no. 1 (2021): 153–59. http://dx.doi.org/10.1353/wam.2021.0012.

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45

Lock, J. M., Camilla R. Huxley, and David F. Cutler. "Ant-Plant Interactions." Kew Bulletin 50, no. 1 (1995): 182. http://dx.doi.org/10.2307/4114630.

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46

Chiou, Yu-Chiun, and Shih-Ta Chou. "Ant Custering Algorithms." International Journal of Applied Evolutionary Computation 1, no. 1 (January 2010): 1–15. http://dx.doi.org/10.4018/jaec.2010010101.

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This paper proposes three ant clustering algorithms (ACAs): ACA-1, ACA-2 and ACA-3. The core logic of the proposed ACAs is to modify the ant colony metaheuristic by reformulating the clustering problem into a network problem. For a clustering problem of N objects and K clusters, a fully connected network of N nodes is formed with link costs, representing the dissimilarity of any two nodes it connects. K ants are then to collect their own nodes according to the link costs and following the pheromone trail laid by previous ants. The proposed three ACAs have been validated on a small-scale problem solved by a total enumeration method. The solution effectiveness at different problem scales consistently shows that ACA-2 outperforms among these three ACAs. A further comparison of ACA-2 with other commonly used clustering methods, including agglomerative hierarchy clustering algorithm (AHCA), K-means algorithm (KMA) and genetic clustering algorithm (GCA), shows that ACA-2 significantly outperforms them in solution effectiveness for the most of cases and also performs considerably better in solution stability as the problem scales or the number of clusters gets larger.

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47

Stafford, Chester T. "Fire Ant Allergy." Allergy and Asthma Proceedings 13, no. 1 (January 1, 1992): 11–16. http://dx.doi.org/10.2500/108854192778878971.

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48

Michael, Loizos. "Ant-Based Computing." Artificial Life 15, no. 3 (July 2009): 337–49. http://dx.doi.org/10.1162/artl.2009.15.3.michael.008.

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A biologically and physically plausible model for ants and pheromones is proposed. It is argued that the mechanisms described in this model are sufficiently powerful to reproduce the necessary components of universal computation. The claim is supported by illustrating the feasibility of designing arbitrary logic circuits, showing that the interactions of ants and pheromones lead to the expected behavior, and presenting computer simulation results to verify the circuits' working. The conclusions of this study can be taken as evidence that coherent deterministic and centralized computation can emerge from the collective behavior of simple distributed Markovian processes such as those followed by biological ants, but also, more generally, by artificial agents with limited computational and communication abilities.

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49

Kercheval, Jesse Lee. "Hormiga, and: Ant." Cream City Review 37, no. 1 (2013): 49–52. http://dx.doi.org/10.1353/ccr.2013.0009.

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50

Levy, Arden L., Jeffrey M. Wagner, and Stanley H. Schuman. "Fire Ant Anaphylaxis." Journal of Agromedicine 5, no. 4 (March 29, 1999): 49–54. http://dx.doi.org/10.1300/j096v05n04_05.

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Artículos de revistas sobre el tema "Ant"

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