AIMC Topic: Predatory Behavior

Clear Filters Showing 1 to 10 of 29 articles

Machine learning and bifurcation analysis in a discrete predator-prey model with neem-induced mortality.

Scientific reports
This study develops a discrete-time predator-prey model for guava pest management using the piecewise constant argument (PCA) scheme. The model incorporates logistic prey growth, neem-induced mortality, and predator crowding. Analytical and numerical...

Optimized hierarchical CLSTM model for sentiment classification of tweets using boosted killer whale predation strategy.

Scientific reports
Opinion mining is more challenging than it was before because of all the user-generated material on social media. People use Twitter (X) to gather opinions on products, advancements, and laws. Sentiment Analysis (SA) examines people's thoughts, feeli...

Diverse prey capture strategies in teleost larvae.

eLife
Animal behavior is adapted to the sensory environment in which it evolved, while also being constrained by physical limits, evolutionary history, and developmental trajectories. The hunting behavior of larval zebrafish (), a cyprinid native to stream...

Collaborative hunting in artificial agents with deep reinforcement learning.

eLife
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
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)
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
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
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
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
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...