AIMC Topic: Predatory Behavior
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Collaborative hunting in artificial agents with deep reinforcement learning.
eLife
May 7, 2024
Collaborative hunting, in which predators play different and complementary roles to capture prey, has been traditionally believed to be an advanced hunting strategy requiring large brains that involve high-level cognition. However, recent findings th...
A robotic falcon induces similar collective escape responses in different bird species.
Journal of the Royal Society, Interface
May 1, 2024
Patterns of collective escape of a bird flock from a predator are fascinating, but difficult to study under natural conditions because neither prey nor predator is under experimental control. We resolved this problem by using an artificial predator (...
Vision-Based Module for Herding with a Sheepdog Robot.
Sensors (Basel, Switzerland)
Jul 16, 2022
Livestock farming is assisted more and more by technological solutions, such as robots. One of the main problems for shepherds is the control and care of livestock in areas difficult to access where grazing animals are attacked by predators such as t...
Responsive robotic prey reveal how predators adapt to predictability in escape tactics.
Proceedings of the National Academy of Sciences of the United States of America
Jun 3, 2022
To increase their chances of survival, prey often behave unpredictably when escaping from predators. However, the response of predators to, and hence the effectiveness of, such tactics is unknown. We programmed interactive prey to flee from an approa...
Competency of Neural Networks for the Numerical Treatment of Nonlinear Host-Vector-Predator Model.
Computational and mathematical methods in medicine
Oct 4, 2021
The aim of this work is to introduce a stochastic solver based on the Levenberg-Marquardt backpropagation neural networks (LMBNNs) for the nonlinear host-vector-predator model. The nonlinear host-vector-predator model is dependent upon five classes, ...
Archerfish respond to a hunting robotic conspecific.
Biological cybernetics
Jul 17, 2021
While the unique hunting behavior of archerfish has received considerable scientific attention, the specific social cues that govern behaviors like intraspecific kleptoparasitism in the species are less understood. This paper asks whether the use of ...
Spider webs inspiring soft robotics.
Journal of the Royal Society, Interface
Nov 11, 2020
In soft robotics, bio-inspiration ranges from hard- to software. Orb web spiders provide excellent examples for both. Adapted sensors on their legs may use morphological computing to fine-tune feedback loops that supervise the handling and accurate p...
Application of machine learning to identify predators of stocked fish in Lake Ontario: using acoustic telemetry predation tags to inform management.
Journal of fish biology
Nov 3, 2020
Understanding predator-prey interactions and food web dynamics is important for ecosystem-based management in aquatic environments, as they experience increasing rates of human-induced changes, such as the addition and removal of fishes. To quantify ...
Skin cancer diagnosis based on optimized convolutional neural network.
Artificial intelligence in medicine
Nov 8, 2019
Early detection of skin cancer is very important and can prevent some skin cancers, such as focal cell carcinoma and melanoma. Although there are several reasons that have bad impacts on the detection precision. Recently, the utilization of image pro...
Design and development of a robotic predator as a stimulus in conditioned place aversion for the study of the effect of ethanol and citalopram in zebrafish.
Behavioural brain research
Oct 12, 2019
Zebrafish are becoming a species of choice in psychopharmacology, laying a promising path to refined pharmacological manipulations and high-throughput behavioral phenotyping. The field of robotics has the potential to accelerate progress along this p...
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