AIMC Topic: Behavior, Animal

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A critique of pure learning and what artificial neural networks can learn from animal brains.

Nature communications
Artificial neural networks (ANNs) have undergone a revolution, catalyzed by better supervised learning algorithms. However, in stark contrast to young animals (including humans), training such networks requires enormous numbers of labeled examples, l...

Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio.

PloS one
Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed g...

An automatic behavior recognition system classifies animal behaviors using movements and their temporal context.

Journal of neuroscience methods
Animals can perform complex and purposeful behaviors by executing simpler movements in flexible sequences. It is particularly challenging to analyze behavior sequences when they are highly variable, as is the case in language production, certain type...

Quadrotor Identification through the Cooperative Particle Swarm Optimization-Cuckoo Search Approach.

Computational intelligence and neuroscience
This paper explores the model parameters estimation of a quadrotor UAV by exploiting the cooperative particle swarm optimization-cuckoo search (PSO-CS). The PSO-CS regulates the convergence velocity benefiting from the capabilities of social thinking...

Photomorphogenesis for robot self-assembly: adaptivity, collective decision-making, and self-repair.

Bioinspiration & biomimetics
Self-assembly in biology is an inspiration for engineered large-scale multi-modular systems with desirable characteristics, such as robustness, scalability, and adaptivity. Previous works have shown that simple mobile robots can be used to emulate an...

Termite population size estimation based on termite tunnel patterns using a convolutional neural network.

Mathematical biosciences
Subterranean termites live in large colonies under the ground where they build an elaborate network of tunnels for foraging. In this study, we explored how the termite population size can be estimated using partial information on tunnel patterns. To ...

Q&A: Understanding the composition of behavior.

BMC biology
Understanding the brain requires understanding behavior. New machine vision and learning techniques are poised to revolutionize our ability to analyze behaviors exhibited by animals in the laboratory. Here we describe one such method, Motion Sequenci...

A force-measuring and behaviour-recording system consisting of 24 individual 3D force plates for the study of single limb forces in climbing animals on a quasi-cylindrical tower.

Bioinspiration & biomimetics
This study describes the design of a new force measuring array with a quasi-cylindrical surface for measuring the 3D ground reaction forces of animals climbing on a surface with high curvature. This force-measuring array was assembled from 24 individ...

Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning.

Nature biomedical engineering
Preclinical studies of psychiatric disorders use animal models to investigate the impact of environmental factors or genetic mutations on complex traits such as decision-making and social interactions. Here, we introduce a method for the real-time an...

Self-supervised learning of the biologically-inspired obstacle avoidance of hexapod walking robot.

Bioinspiration & biomimetics
In this paper, we propose an integrated biologically inspired visual collision avoidance approach that is deployed on a real hexapod walking robot. The proposed approach is based on the Lobula giant movement detector (LGMD), a neural network for loom...