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Perspectives on the Use of Robots in Etho-experimental Approaches to Animal Behavior

심리학 및 행동생물학적 연구에서 동물 로봇의 활용과 전망

  • Received : 2022.01.13
  • Accepted : 2022.01.17
  • Published : 2022.02.28

Abstract

Utilization of small robots in psychology and biology provides a new breakthrough in understanding the neurobiological mechanisms of various animal behavior. The expansion of robot use in animal research is partly due to increased availability of economically plausible mobile robots and also due to the current shift in animal research toward more ecologically valid experiments. Ground-breaking experimental findings are expected when the behavioral variables are manipulated in more natural situations. In addition, the results from laboratory could be generalized more easily with added ecological validity. The current paper attempts to review a wide range of applications of animal robots used to study animal behavior and to highlight major advantages and limitations. In particular, this review focuses more on the psychological impact of animal robots than engineering details about their structure and operation. Finally, this review will provide some practical considerations when employing robots in animal experiments.

Keywords

Acknowledgement

This study was supported by a faculty research grant from the College of Liberal Arts at Korea University in 2018

References

  1. I. P. Pavlov, Conditioned Reflexes: An Investigation of the Physiological Activity of the Cerebral Cortex. London: Oxford University Press, 1927, DOI: 10.1093/brain/51.1.129.
  2. E. L. Thorndike, Animal Intelligence: Experimental Studies. New York: Macmillan Company, 1911, [Online], https://openlibrary.org/books/OL7172495M/Animal_intelligence.
  3. E. R. Kandel, "The molecular biology of memory: cAMP, PKA, CRE, CREB-1, CREB-2, and CPEB," Mol. Brain, vol. 5, no. 14, pp. 1-12, May, 2012, DOI: 10.1186/1756-6606-5-14.
  4. W. Schultz, P. Dayan, and P. R. Montague, "A neural substrate of prediction and reward," Science, vol. 275, no. 5306, pp. 1593-1599, March, 1997, DOI: 10.1126/science.275.5306.1593.
  5. R. S. Sutton and A. G. Barto, Reinforcement Learning: An Introduction. 2nd ed., Cambridge: The MIT Press, November, 2018, [Online], https://web.stanford.edu/class/psych209/Readings/SuttonBartoIPRLBook2ndEd.pdf.
  6. K. Lorenz, "Der Kumpan in der Umwelt des Vogels," J. Ornithol, vol. 83, pp. 137-213, April, 1935, [Online], http://klha.at/papers/1935-Kumpan.pdf. https://doi.org/10.1007/BF01905355
  7. K. V. Frisch, The Dance Language and Orientation of Bees. Cambridge: Harvard University Press, January, 1993, [Online], https://www.degruyter.com/document/doi/10.4159/harvard.9780674418776/html
  8. N. Tinbergen, "The Curious Behavior of the Stickleback," Scientific American, vol. 187, no. 6, pp. 22-27, December, 1952, [Online], https://www.jstor.org/stable/24944080. https://doi.org/10.1038/scientificamerican1252-22
  9. D. Morris, The Naked Ape., New York: Dell Publishing, October, 1967, [Online], https://folk.ntnu.no/krill/bioko-references/Morris%201967.pdf
  10. D. C. Blanchard and R. J. Blanchard, "Ethoexperimental approaches to the biology of emotion," Annu. Rev. Psychol., vol. 39, pp. 43-68, February, 1988, DOI: 10.1146/annurev.ps.39.020188. 000355.
  11. B. A. Pellman and J. J. Kim, "What can ethobehavioral studies tell us about the brain's fear systems?," Trends Neurosci., vol. 39, no. 6, pp. 420-431, June, 2016, DOI: 10.1016/j.tins.2016.04.001.
  12. J. Halloy, G. Sempo, G. Caprari, C. Rivault, M. Asadpour, F. Ta che, I. Said, V. Durier, S. Canonge, J. M. Ame, C. Detrain, N. Correll, A. Martinoli, F. Mondada, R. Siegwart, and J. L. Deneubourg, "Social integration of robots into groups of cockroaches to control self-organized choices," Science, vol. 318, no. 5853, pp. 1155-1158, November, 2007, DOI: 10.1126/science.1144259.
  13. J.-D, Choi and J. J. Kim, "Amygdala regulates risk of predation in rats foraging in a dynamic fear environment," Proc Natl Acad Sci USA, vol. 107, no. 50, pp. 21773-21777, December, 2010, DOI: 10.1073/pnas.1010079108.
  14. W. G. Walter, "A machine that learns," Scientific American, vol. 184, no. 8, pp. 60-63, August, 1951, [Online], https://www.scientificamerican.com/article /a-machine-that-learns/. https://doi.org/10.1038/scientificamerican0851-60
  15. R. Brooks, Flesh and Machines: How Robots Will Change Us. New York: Vintage Books, February, 2003, [Online], https://www.semanticscholar.org/paper/Flesh-and-Machines%3A-How-Robots-Will-Change-Us-Brooks/8879847b07fac6fe93c39b7bb016b0fada227e4d#citing-papers.
  16. H. F. Harlow, "Affectional Response in the infant monkey," Science, vol.130, no.3373, pp.421-432, August, 1959, DOI: 10.1126/science.130.3373.421.
  17. Q. Shi, H. Ishii, K. Tanaka, Y. Sugahara, A. Takanishi, S. Okabayashi, Q. Huang, and T. Fukuda, "Behavior modulation of rats to a robotic rat in multi-rat interaction," Bioinspiration & biomimetics, vol. 10, no. 5, 2015, DOI: 10.1088/1748-3190/10/5/056011
  18. H. Ishii, Q. Shi, S. Fumino, S. Konno, S. Kinoshita, S. Okabayashi, N. Iida, H. Kimura, Y. Tahara, S. Shibata, and A. Takanishi, "A novel method to develop an animal model of depression using a small mobile robot," Advanced Robotics, vol. 27, no. 1, pp. 61-69, 2012, DOI: 10.1080/01691864.2013.752319.
  19. S. Butail, N. Abaid, S. Macri, and M. Porfiri, "Fish-Robot Interactions: Robot Fish in Animal Behavioral Studies," Robot Fish, pp. 359-377, May 2015, DOI: 10.1007/978-3-662-46870-8_12.
  20. C. Spinello, Y. Yang, S. Macri, and M. Porfiri, "Zebrafish Adjust Their Behavior in Response to an Interactive Robotic Predator," Frontiers in Robotics and AI, vol. 6, no. 38, May, 2019, DOI: 10.3389/frobt.2019.00038.
  21. A. S. Rundus, D. H. Owings, S. S. Joshi, E. Chinn, and N. Giannini, "Ground squirrels use an infrared signal to deter rattlesnake predation," National Academy of Sciences, vol. 104, no. 36, pp. 14372-14376, 2007, DOI: 10.1073/pnas.0702599104.
  22. J. Kim, C. Kim, H.-B. Han, C. J. Cho, W. Yeom, S. Q. Lee, and J. H. Choi, "A bird's-eye view of brain activity in socially interacting mice through mobile edge computing (MEC)," Science Advances, vol. 6, no. 49, 2020, DOI: 10.1126/sciadv.abb9841.
  23. M. Davila-Ross, J. Hutchinson, J. L. Russell, J. Schaeffer, A. Billard, W. D. Hopkins, and K. A. Bard, "Triggering social interactions: chimpanzees respond to imitation by a humanoid robot and request responses from it," Animal Cognition, vol. 17, no. 3, pp. 589-595, May, 2014, DOI: 10.1007/s10071-013-0689-9.
  24. P. M. Narins, D. S. Grabul, K. K. Soma, P. Gaucher, and W. Hodl, "Cross-modal integration in a dart-poison frog," National Academy of Sciences, vol. 102, no. 7, pp. 2425-2429, February, 2005, DOI: 10.1073/pnas.0406407102.
  25. R. del A. Oritz, C. M. Contreras, A. G. Gutierrez-Garcia, and F. M. Gonzalez, "Social Interaction Test between a Rat and a Robot: A Pilot Study," International Journal of Advanced Robotic Systems, vol. 13, no. 4, pp. 1-10, January, 2016, DOI: 10. 5772/62015. https://doi.org/10.5772/62015
  26. L. K. Quinn, L. P. Schuster, M. Aguilar-Rivera, J. Arnold, D. Ball, E. Gygi, J. Holt, D. J Lee, J. Taufatofua, J. Wiles, and A. A. Chiba, "When rats rescue robots," Animal Behavior and Cognition, vol. 5, no. 4, pp. 368-379, November, 2018, DOI: 10.26451/abc.05.04.04.2018.
  27. E. de Margerie, S. Lumineau, C. Houdelier, and M.-R. Richard Yris, "Influence of a mobile robot on the spatial behaviour of quail chicks," Bioinspiration & Biomimetics, vol. 6, no. 3, September, 2011, DOI: 10. 1088/1748-3182/6/3/034001. https://doi.org/10.1088/1748-3182/6/3/034001
  28. A. Amir, S.-C. Lee, D. B. Headley, M. M. Herzallah, and D. Pare, "Amygdala Signaling during Foraging in a Hazardous Environment," Journal of Neuroscience, vol. 35, no. 38, pp. 12994-13005, November, 2015, DOI: 10.1523/JNEUROSCI.0407-15.2015.
  29. J. H. Lee, S. Kimm, J. S. Han, and J. S. Choi, "Chasing as a model of psychogenic stress: characterization of physiological and behavioral responses," Stress, vol. 21, no. 4, pp. 323-332, July, 2018, DOI: 10.1080/10253890.2018.1455090.
  30. S. Kimm and J.-S. Choi. "Sensory and motivational modulation of immediate and delayed defensive responses under dynamic threat," J. Neurosci Methods, vol. 307, pp. 84-94, September, 2018, DOI: 10.1016/j.jneumeth.2018.06.023.
  31. T. Park and Y. Cha. "Soft mobile robot inspired by animal-like running motion," Scientific Reports, vol. 9, no. 14700, pp. 1-9, October, 2019, DOI: 10.1038/s41598-019-51308-4.