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Animal learning has interested ecologists and psychologists for over a century. Mathematical models that explain how animals store and recall information have gained attention recently. Central to this work is statistical decision theory…

Quantitative Methods · Quantitative Biology 2022-08-29 Peter R. Thompson , Melodie Kunegel-Lion , Mark A. Lewis

Many animals possess a remarkable capacity to rapidly construct flexible cognitive maps of their environments. These maps are crucial for ethologically relevant behaviors such as navigation, exploration, and planning. Existing computational…

Artificial Intelligence · Computer Science 2026-02-04 Zizhan He , Maxime Daigle , Pouya Bashivan

Living in groups brings benefits to many animals, such as a protection against predators and an improved capacity for sensing and making decisions while searching for resources in uncertain environments. A body of studies has shown how…

Populations and Evolution · Quantitative Biology 2019-01-23 Andrea Falcón-Cortés , Denis Boyer , Gabriel Ramos-Fernández

We view random walks as the paths of foraging animals, perhaps searching for food or avoiding predators while forming a mental map of their surroundings. The formation of such maps requires them to memorise the locations they have visited.…

Probability · Mathematics 2018-08-24 Michal Gnacik , Abdulrahman Alsolami , James Burridge

In order to explore and act autonomously in an environment, an agent needs to learn from the sensorimotor information that is captured while acting. By extracting the regularities in this sensorimotor stream, it can learn a model of the…

Artificial Intelligence · Computer Science 2018-04-27 Thibaut Kulak , Michael Garcia Ortiz

Animal movement exhibits complex behavior which can be influenced by unobserved environmental conditions. We propose a model which allows for a spatially-varying movement rate and spatially-varying drift through a semiparametric potential…

Applications · Statistics 2017-02-28 James C. Russell , Ephraim M. Hanks , Murali Haran , David P. Hughes

A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. However, the role played by the environment in influencing the…

Neural and Evolutionary Computing · Computer Science 2018-04-23 Andreas Steyven , Emma Hart , Ben Paechter

Spatiotemporal dynamics models are fundamental for various domains, from heat propagation in materials to oceanic and atmospheric flows. However, currently available neural network-based spatiotemporal modeling approaches fall short when…

Machine Learning · Computer Science 2025-02-11 Valerii Iakovlev , Harri Lähdesmäki

The study of animal movement is challenging because it is a process modulated by many factors acting at different spatial and temporal scales. Several models have been proposed which differ primarily in the temporal conceptualization,…

A suite of statistical methods are used to study animal movement. Most of these methods treat animal telemetry data in one of three ways: as discrete processes, as continuous processes, or as point processes. We briefly review each of these…

Methodology · Statistics 2019-12-20 Mevin B. Hooten , Xinyi Lu , Martha J. Garlick , James A. Powell

Collective phenomena, whereby agent-agent interactions determine spatial patterns, are ubiquitous in the animal kingdom. On the other hand, movement and space use are also greatly influenced by the interactions between animals and their…

Quantitative Methods · Quantitative Biology 2016-03-21 Jonathan R. Potts , Karl Mokross , Mark A. Lewis

1. Animal movement patterns contribute to our understanding of variation in breeding success and survival of individuals, and the implications for population dynamics. 2. Over time, sensor technology for measuring movement patterns has…

Quantitative Methods · Quantitative Biology 2018-01-11 Leah R. Johnson , Philipp H. Boersch-Supan , Richard A. Phillips , Sadie J. Ryan

Robotic and animal mapping systems share many challenges and characteristics: they must function in a wide variety of environmental conditions, enable the robot or animal to navigate effectively to find food or shelter, and be…

Robotics · Computer Science 2017-12-25 Litao Yu , Adam Jacobson , Michael Milford

Place recognition, the ability to identify previously visited locations, is critical for both biological navigation and autonomous systems. This review synthesizes findings from robotic systems, animal studies, and human research to explore…

Robotics · Computer Science 2025-11-19 Michael Milford , Tobias Fischer

Nature is in constant flux, so animals must account for changes in their environment when making decisions. How animals learn the timescale of such changes and adapt their decision strategies accordingly is not well understood. Recent…

Neurons and Cognition · Quantitative Biology 2018-12-24 Zachary P. Kilpatrick , William R. Holmes , Tahra L. Eissa , Krešimir Josić

We consider the general problem of modeling temporal data with long-range dependencies, wherein new observations are fully or partially predictable based on temporally-distant, past observations. A sufficiently powerful temporal model…

Temporal resolution of visual information processing is thought to be an important factor in predator-prey interactions, shaped in the course of evolution by animals' ecology. Here I show that light can be considered to have a dual role of…

Neurons and Cognition · Quantitative Biology 2019-10-25 Bartosz Jura

We explore how different types and uses of memory can aid spatial navigation in changing uncertain environments. In the simple foraging task we study, every day, our agent has to find its way from its home, through barriers, to food.…

Artificial Intelligence · Computer Science 2026-02-18 Omid Madani , J. Brian Burns , Reza Eghbali , Thomas L. Dean

Animal behavior serves as a reliable indicator of the adaptation of organisms to their environment and their overall well-being. Through rigorous observation of animal actions and interactions, researchers and observers can glean valuable…

Machine Learning · Computer Science 2024-05-24 Edoardo Fazzari , Donato Romano , Fabrizio Falchi , Cesare Stefanini

In the mammalian brain, many neuronal ensembles are involved in representing spatial structure of the environment. In particular, there exist cells that encode the animal's location and cells that encode head direction. A number of studies…

Neurons and Cognition · Quantitative Biology 2021-08-10 Y. Dabaghian