Predicting Theropod Hunting Tactics using Machine Learning.

Matthew Millar


The use of machine learning in different fields is becoming a more common practice thanks to Big Data and better granularity in data being collected. The application of machine learning to animal behavioral pattern analysis is becoming more popular due to the increase in size, types, and quality of data that can be gathered. Machine learning can even be used to predict the actual behavior of animals based off of certain features. This approach can also be used for predicting the behavior of extinct animals. This paper is the goal is to explore the possibility of using machine learning techniques to predict the hunting habits of dinosaurs based solely off of physical characteristic of the animal. By using the biomechanical features, a model can be created to aid in the classification of animals into either a scavenger or hunter roles. The results from the test show that there is a strong correlation between the physical characteristics and potential hunting habits. The models used here can then be used as a good baseline in predicting other theropods based solely on their bodies. The T-Rex was used as the test subject and was correctly classified as a primary hunter in most of the models.


Machine Learning; artificial intelligence; animal behavior modeling; tyrannosaurus Rex; hunting behavior modeling

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: Horner, J. Dinosaur behavior and growth. The Paleontological Society Special Publications; 1992, 6, 135-135.

: Chiappe, LM. A Field Trip to the Mesozoic. PLOS Biology; 2003 1(2): e40.

: Tanke, D. Currie, P. Head-Biting Behavior In Theropod Dinosaurs: Paleopathological Evidence. gaia: Okologische Perspektiven in Natur-, Geistes- Und Wirtschaftswissenschaften; 2000, 15, 167-183.

: Holtz, T.R. A Critical Reappraisal of the Obligate Scavenging Hypothesis for Tyrannosaurus rex and Other Tyrant Dinosaurs. in Larson, P. and Carpenter, K. (eds) Tyrannosaurus rex: The Tyrant King. Bloomington: Indiana University Press; 2008.

: DeVault, T. Rhodes, O. Shivik, J. Scavenging by vertebrates: behavioral, ecological, and evolutionary perspectives on an important energy transfer pathway in terrestrial ecosystems. USDA National Wildlife Research Center - Staff Publications; 2003, 269.

: Sherman, P. W., & Seeley, T. D. Animal behaviour. Retrieved July 23, 2018, from; 2017.

: McGreevy, P. Boakes, R. Carrots and Sticks; Principles of Animal Training. Darlington Press; 2011. Pg xi-23.

: Immelmann, K. (). Aims, Methods, and Areas of Ethology. Introduction to Ethology; 1980 ,1-9.

: Boakes, R. From Darwin to behaviourism: Psychology and the minds of animals. Cambridge: Cambridge University Press; 1988 .

: Anderson , D. Perona , P. Toward a Science of Computational Ethology, Neuron,; 2014 Volume 84, Issue 1, Pages 18-31.

: Valletta, J. J., Torney, C., Kings, M., Thornton, A., & Madden, J. Applications of machine learning in animal behaviour studies. Animal Behaviour; 2017,124, 203-220.

: Schank J., Joshi S., May C., Tran J.T., Bish R. A Multi-Modeling Approach to the Study of Animal Behavior. In: Minai A.A., Braha D., Bar-Yam Y. (eds) Unifying Themes in Complex Systems. Springer, Berlin, Heidelberg; 2011.

: Castro, J. Tyrannosaurus Rex: Facts About T. Rex, King of the Dinosaurs. Retrieved July 19, 2018, from; 2017.

: Hutchinson, JR. Bates, KT. Molnar, J. Allen, V. Makovicky, PJ. A computational Analysis of Limb and Body Dimensions in Tyrannosaurus Rex with Implications for Locomotion, Ontogeny, and Growth. PLoS One; 2011, vol 6 10

: Longrich , N., Horner, J., Erickson, G., & Currie, P. Cannibalism in Tyrannosaurus rex. PloSOne; 2010. 5(10): e13419

: Horner, J., Goodwin, M., & Myhrvold, N. Dinosaur Census Reveals Abundant Tyrannosaurus and Rare Ontogenetic Stages in the Upper Cretaceous Hell Creek Formation (Maastrichtian), Montana, USA PLoS ONE; 2011, 6 (2)

: Hutchinson, John. Tyrannosaurus rex: predator or media hype?. What's in John's Freezer? Retrieved August 26, 2013.

: Kane, A. Healy, K. Ruxton, G. Jackson, A. "Body Size as a Driver of Scavenging in Theropod Dinosaurs" . The American Naturalist; 2016, 187(6).

: Altman, N. S. An introduction to kernel and nearest-neighbor nonparametric regression. The American Statistician; 1992, 46(3): 175–185.

: Walker, SH. Duncan, DB. Estimation of the probability of an event as a function of several independent variables. Biometrika; 1967. 54: 167–178.

: Cortes, Corinna; Vapnik, Vladimir N. Support-vector networks. Machine Learning; 1995, 20 (3): 273–297.

: Blei, David M.; Ng, Andrew Y.; Jordan, Michael. Lafferty, John, ed. Latent Dirichlet Allocation. Journal of Machine Learning Research; 2003. 3 (4–5): pp. 993–1022

: Quinlan, J. R. Simplifying decision trees. International Journal of Man-Machine Studies; 1987, 27 (3): 221.

: Russell, Stuart; Norvig, Peter. Artificial Intelligence: A Modern Approach (2nd ed.). Prentice Hall; 2003.



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