Relevant bibliographies by topics / Associative learning in spiders

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Academic literature on the topic 'Associative learning in spiders'

Author: Grafiati
Published: 10 December 2022
Last updated: 31 July 2025

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Journal articles on the topic "Associative learning in spiders"

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Su, Yong-Chao, Cheng-Yu Wu, Cheng-Hong Yang, Bo-Sheng Li, Sin-Hua Moi, and Yu-Da Lin. "Machine Learning Data Imputation and Prediction of Foraging Group Size in a Kleptoparasitic Spider." Mathematics 9, no. 4 (2021): 415. http://dx.doi.org/10.3390/math9040415.

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Cost–benefit analysis is widely used to elucidate the association between foraging group size and resource size. Despite advances in the development of theoretical frameworks, however, the empirical systems used for testing are hindered by the vagaries of field surveys and incomplete data. This study developed the three approaches to data imputation based on machine learning (ML) algorithms with the aim of rescuing valuable field data. Using 163 host spider webs (132 complete data and 31 incomplete data), our results indicated that the data imputation based on random forest algorithm outperfor
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Haselgrove, Mark. "Overcoming associative learning." Journal of Comparative Psychology 130, no. 3 (2016): 226–40. http://dx.doi.org/10.1037/a0040180.

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Shanks, David R. "Bayesian associative learning." Trends in Cognitive Sciences 10, no. 11 (2006): 477–78. http://dx.doi.org/10.1016/j.tics.2006.09.004.

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Shanks, David R. "The associative nature of human associative learning." Behavioral and Brain Sciences 32, no. 2 (2009): 225–26. http://dx.doi.org/10.1017/s0140525x09001149.

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AbstractThe extent to which human learning should be thought of in terms of elementary, automatic versus controlled, cognitive processes is unresolved after nearly a century of often fierce debate. Mitchell et al. provide a persuasive review of evidence against automatic, unconscious links. Indeed, unconscious processes seem to play a negligible role in any form of learning, not just in Pavlovian conditioning. But a modern connectionist framework, in which “cognitive” phenomena are emergent properties, is likely to offer a fuller account of human learning than the propositional framework Mitch
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Volbrecht, Vicki J. "Perceptual learning meets associative learning." New Ideas in Psychology 11, no. 2 (1993): 285–86. http://dx.doi.org/10.1016/0732-118x(93)90042-c.

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Moore, John W., and Geoffrey Hall. "Perceptual and Associative Learning." American Journal of Psychology 107, no. 3 (1994): 465. http://dx.doi.org/10.2307/1422887.

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Balsam, Peter, Michael Drew, and C. Gallistel. "Time and Associative Learning." Comparative Cognition & Behavior Reviews 5 (2010): 1–22. http://dx.doi.org/10.3819/ccbr.2010.50001.

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Hummel, John E. "Symbolic Versus Associative Learning." Cognitive Science 34, no. 6 (2010): 958–65. http://dx.doi.org/10.1111/j.1551-6709.2010.01096.x.

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Hawkins, Robert D., and John H. Byrne. "Associative Learning in Invertebrates." Cold Spring Harbor Perspectives in Biology 7, no. 5 (2015): a021709. http://dx.doi.org/10.1101/cshperspect.a021709.

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Bennet, Alex, and David Bennet. "Learning as associative patterning." VINE 36, no. 4 (2006): 371–76. http://dx.doi.org/10.1108/03055720610716638.

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Dissertations / Theses on the topic "Associative learning in spiders"

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Shannon, Hailey C. "Learning and foraging in the wolf spider Pardosa milvina (Araneae: Lycosidae)." Miami University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=miami1595945122268994.

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Bosshard, Tiffany Claire. "Cognition in black-handed spider monkeys (Ateles geoffroyi): A battery of behavioral tests." Thesis, Linköpings universitet, Institutionen för fysik, kemi och biologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-171412.

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Cognition allows animals to acquire, process, and store sensory information from the environment and use it to adapt to their surroundings. A battery of behavioral tests was used to assess the cognitive abilities of black-handed spider monkeys (Ateles geoffroyi). Black and white cups were used to assess (1) object permanence by showing the animals under which cup the reward was placed, (2) associative learning by concealing where the reward was placed, and (3) long-term memory by repeating the second task after a 4-month break; petri dishes with varying amounts of food were used to assess (4)
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Ray, Elizabeth Deborah. "Social and associative learning." Thesis, University College London (University of London), 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.266406.

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Vaughn, Kalif Elijah. "CRITERION LEARNING AND ASSOCIATIVE MEMORY GAINS: EVIDENCE AGAINST ASSOCIATIVE SYMMETRY." Kent State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=kent1342117558.

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Press, C. M. "Automatic imitation and associative learning." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1446047/.

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Human body movements are especially effective in eliciting imitative responses. This thesis aims to establish why this is the case, and fundamentally, what this suggests about the mechanisms mediating imitation. Chapter 1 outlines theories which can account for this imitative bias, and highlights issues upon which these theories can be distinguished. Chapter 2 establishes whether the finding that responses are executed faster in response to stimuli of the same action type reflects an automatic tendency to imitate observed actions. On the basis of evidence to support this hypothesis, Chapters 3
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Millington, Peter J. (Peter John). "Associative reinforcement learning for optimal control." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/13830.

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Jones, Alexander. "Spiking Neuromorphic Architecture for Associative Learning." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613685923717444.

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Kan, Wing Kay. "A probabilistic neural network for associative learning." Thesis, Imperial College London, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.283809.

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Grand, Christopher S. "Perceptual and functional categorisation in associative learning." Thesis, Cardiff University, 2007. http://orca.cf.ac.uk/54587/.

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This thesis investigated the theoretical processes that underlie perceptual and functional categorisation: perceptual categorisation refers to the process of forming an integrated representation of a pattern of stimulation and functional categorisation refers to the process of integrating otherwise equivalent patterns of stimulation according to their uses or consequences. Investigation of perceptual categorisation in people and of functional categorisation in rats provided results that place important constraints on the nature of the involvement of elemental and configural processes.
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Du, Wenchong. "Associative implicit learning in adult dyslexic readers." Thesis, University of Strathclyde, 2013. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=20828.

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This thesis examined associative implicit learning in dyslexic young adults. Dyslexic adults' associative implicit learning has been examined from three perspectives: what, when, and how. More specifically, it has been investigated if dyslexics have deficit in learning more complex knowledge, such as longer chunks or abstract knowledge (i.e., 'what'); if learning occurs at different stages in dyslexics compared to non-dyslexics (i.e., when); how dyslexics learn, and especially the role of both implicit and explicit processes (i.e., 'how'). The empirical findings from 9 experiments in 5 studies
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Books on the topic "Associative learning in spiders"

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J, Wills A., ed. New directions in human associative learning. Lawrence Erlbaum, 2004.

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Schmajuk, Nestor A., and Peter C. Holland, eds. Occasion setting: Associative learning and cognition in animals. American Psychological Association, 1998. http://dx.doi.org/10.1037/10298-000.

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Nestor, Schmajuk, Holland Peter C. 1951-, and American Psychological Association, eds. Occasion setting: Associative learning and cognition in animals. American Psychological Association, 1998.

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1967-, Meira Wagner, ed. Demand-driven associative classification. Springer, 2011.

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Olds, James. A role for protein kinase C in associative learning. National Institute of Neurological and Communicative Disorders and Stroke, 1993.

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Kyllonen, Patrick C. Knowledge and processing speed as determinants of associative learning. Air Force Human Resources Laboratory, Air Force Systems Command, 1989.

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Gary, Lupyan, Oakes Lisa M. 1963-, Walker-Andrews Arlene S, and Collins W. Andrew 1944-, eds. Developing object concepts in infancy: An associative learning perspective. Wiley-Blackwell Pub., 2008.

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Turkcan, Mehmet Kerem. Sensory Processing and Associative Learning in Connectome-Based Neural Circuits. [publisher not identified], 2022.

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Morrison, Glenn Everett. The behavioural and genetic analysis of associative learning and memory in Caenorhabditis elegans. National Library of Canada = Bibliothèque nationale du Canada, 1995.

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Chamizo, V. D. Associative learning and cognition: Homage to Professor N. J. Mackintosh. In memoriam (1935-2015). Universitat de Barcelona, 2016.

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Book chapters on the topic "Associative learning in spiders"

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Jozefowiez, Jeremie. "Associative Learning." In Encyclopedia of the Sciences of Learning. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-1428-6_703.

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Scherrmann, Jean-Michel, Kim Wolff, Christine A. Franco, et al. "Associative Learning." In Encyclopedia of Psychopharmacology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_3079.

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Hangay, George, Severiano F. Gayubo, Marjorie A. Hoy, et al. "Associative Learning." In Encyclopedia of Entomology. Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_10370.

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DeAquair, Rebecca. "Associative Learning." In Encyclopedia of Autism Spectrum Disorders. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1698-3_1005.

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Christoforou, Christoforos. "Associative Learning." In Encyclopedia of Evolutionary Psychological Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-16999-6_1038-1.

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Feng, Shao. "Associative Learning." In The ECPH Encyclopedia of Psychology. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6000-2_63-1.

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Alfaro, Felipe, Javier Bustamante, Simón Ramírez Muñoz, Gonzalo Miguez, Mario A. Laborda, and Rocio Angulo. "Associative Learning." In Encyclopedia of Sexual Psychology and Behavior. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-08956-5_299-1.

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Allen, Colin. "Associative Learning." In The Routledge Handbook of Philosophy of Animal Minds. Routledge, 2017. http://dx.doi.org/10.4324/9781315742250-39.

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Papini, Mauricio R., and Shannon E. Conrad. "Associative Learning." In Encyclopedia of Animal Cognition and Behavior. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47829-6_1067-1.

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Papini, Mauricio R., and Shannon E. Conrad. "Associative Learning." In Encyclopedia of Animal Cognition and Behavior. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_1067.

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Conference papers on the topic "Associative learning in spiders"

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Ivanova, Anna, Dmitry Ivashkin, Ksenia Toropova, Olga Ivashkina, and Konstantin Anokhin. "Behavioral Enhancement of Associative Learning Requires Overlapping Neuronal Populations." In 2024 8th Scientific School Dynamics of Complex Networks and their Applications (DCNA). IEEE, 2024. http://dx.doi.org/10.1109/dcna63495.2024.10718502.

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Liu, Yixi, and Dongyi Wang. "Research on associative learning and memory circuits based on memristors." In 2024 IEEE 6th International Conference on Civil Aviation Safety and Information Technology (ICCASIT). IEEE, 2024. https://doi.org/10.1109/iccasit62299.2024.10827865.

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Qiu, Haoyang, Ke Li, Ling Chen, and Rui Gao. "A Non-associative Learning Emotional Progressive Circuit Based on Forgetting Memristor." In 2024 6th International Conference on Electronic Engineering and Informatics (EEI). IEEE, 2024. http://dx.doi.org/10.1109/eei63073.2024.10696898.

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C, Amutha, and P. Periyasamy. "Prediction of Thyroid Using Three-Stage Rule-Generative Associative Learning Model." In 2024 International Conference on Sustainable Communication Networks and Application (ICSCNA). IEEE, 2024. https://doi.org/10.1109/icscna63714.2024.10864228.

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Smart, Matthew, Stanislav Y. Shvartsman, and Martin Mönnigmann. "A minimal dynamical system and analog circuit for non-associative learning." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10886642.

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Taskar, Ben, Vassil Chatalbashev, and Daphne Koller. "Learning associative Markov networks." In Twenty-first international conference. ACM Press, 2004. http://dx.doi.org/10.1145/1015330.1015444.

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Jonsson, E., and M. Felsberg. "Correspondence-free Associative Learning." In 18th International Conference on Pattern Recognition (ICPR'06). IEEE, 2006. http://dx.doi.org/10.1109/icpr.2006.420.

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Kabir, Md Rayhan, and Osmar R. Zaiane. "Dynamic Ensemble Associative Learning." In 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). IEEE, 2022. http://dx.doi.org/10.1109/asonam55673.2022.10068715.

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Sahay, Avani, and Dr Sunaina Kaur Maan. "From Fear to Familiarity: A Case Study on Overcoming Arachnophobia Through Exposure Therapy." In Transforming Knowledge: A Multidisciplinary Research on Integrative Learning Across Disciplines. The Bhopal School of Social Sciences, 2025. https://doi.org/10.51767/ic250442.

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Arachnophobia, an intense and irrational fear of spiders, is one of the most common specific phobias. This case study examines the psychological, physiological, and behavioral aspects of arachnophobia in a 19-year-old female. The subject exhibits severe anxiety, avoidance behavior, and distress when exposed to spiders or spider-related stimuli. The study explores the underlying cognitive and emotional processes contributing to the phobia, including past trauma, learned associations, and evolutionary predispositions. Treatment approaches such as cognitive-behavioral therapy (CBT), systematic de
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Deng, Zi Kang, and Jeffrey J. Rodriguez. "Look Out for Dangerous Spiders: Araneae Classification Using Deep Learning Methods." In 2024 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI). IEEE, 2024. http://dx.doi.org/10.1109/ssiai59505.2024.10508676.

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Reports on the topic "Associative learning in spiders"

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Lerman, Zafra, and Geof Goldbogen. Hippocampal Modulation of Associative Learning. Defense Technical Information Center, 1992. http://dx.doi.org/10.21236/ada258251.

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Kyllonen, Patrick C., and William C. Tirre. Individual Differences in Associative Learning and Forgetting. Defense Technical Information Center, 1989. http://dx.doi.org/10.21236/ada212765.

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Orbán, Levente. Associative Learning in Psychology: Classical and Operant Conditioning Revisited. Orban Foundation, 2025. https://doi.org/10.69642/5323.

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Learning is a central concept in psychology, governing how organisms adapt to their environments. This paper revisits foundational theories of associative learning, with an emphasis on classical conditioning, as discovered by Ivan Pavlov, and operant conditioning, as developed by B.F. Skinner. Drawing from a transcript of a live undergraduate lecture, we explore theoretical models, empirical evidence, practical examples, and mathematical structures underlying these learning mechanisms. The aim is to distill key insights while highlighting the contemporary relevance of behaviorist principles in
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Daudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe, and Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, 2021. http://dx.doi.org/10.53328/uxuo4751.

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The report provides a review of how risk is conceived of, modelled, and mapped in studies of infectious water, sanitation, and hygiene (WASH) related diseases. It focuses on spatial epidemiology of cholera, malaria and dengue to offer recommendations for the field of WASH-related disease risk mapping. The report notes a lack of consensus on the definition of disease risk in the literature, which limits the interpretability of the resulting analyses and could affect the quality of the design and direction of public health interventions. In addition, existing risk frameworks that consider diseas
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti
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