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The question of how "smart" active agents, like insects, microorganisms, or future colloidal robots need to steer to optimally reach or discover a target, such as an odor source, food, or a cancer cell in a complex environment has recently…

Soft Condensed Matter · Physics 2023-04-05 Mahdi Nasiri , Hartmut Löwen , Benno Liebchen

Recent experimental observations have shown that the reactivation of hippocampal place cells (PC) during sleep or immobility depicts trajectories that can go around barriers and can flexibly adapt to a changing maze layout. Such…

Neurons and Cognition · Quantitative Biology 2022-09-20 Yuanxiang Gao

Locating and intercepting a moving target from possibly delayed, intermittent sensory signals is a paradigmatic problem in decision-making under uncertainty, and a fundamental challenge for, e.g., animals seeking prey or mates and…

This study investigates the dynamics of non-spatial specializations in hippocampal place cells during exposure to novel environments. Hippocampal place cells, known for their role in spatial mapping, exhibit multi-modal responses to sensory…

People make strategic decisions many times a day - during negotiations, when coordinating actions with others, or when choosing partners for cooperation. The resulting dynamics can be studied with learning theory and evolutionary game…

Populations and Evolution · Quantitative Biology 2026-03-26 Marta C. Couto , Fernando P. Santos , Christian Hilbe

The motility of the worm nematode \textit{Caenorhabditis elegans} is investigated in shallow, wet granular media as a function of particle size dispersity and area density ($\phi$). Surprisingly, we find that the nematode's propulsion speed…

Biological Physics · Physics 2012-03-06 G. Juarez , K. Lu , J. Sznitman , P. E. Arratia

Continual learning in computational systems is challenging due to catastrophic forgetting. We discovered a two layer neural circuit in the fruit fly olfactory system that addresses this challenge by uniquely combining sparse coding and…

Machine Learning · Computer Science 2021-12-23 Yang Shen , Sanjoy Dasgupta , Saket Navlakha

Understanding how animals make foraging decisions in challenging or unpleasant contexts sheds light on the processes that underlie cognitive development and the evolution of adaptive foraging techniques in complex ecological settings. In…

Quantitative Methods · Quantitative Biology 2025-04-14 Tuhin Subhra Pal , Prithwiraj Debnath , Sagarika Biswas , Anindita Bhadra

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

The reshaping and decorrelation of similar activity patterns by neuronal networks can enhance their discriminability, storage, and retrieval. How can such networks learn to decorrelate new complex patterns, as they arise in the olfactory…

Neurons and Cognition · Quantitative Biology 2015-06-04 Siu-Fai Chow , Stuart D. Wick , Hermann Riecke

In dynamic flow fields, various animals exhibit remarkable odor search capabilities despite relying on stochastic detections. Interestingly, there exists an optimal time window for integrating these detections that maximizes search…

Machine Learning · Computer Science 2026-05-20 Changxu Zhao , Dongxiao Zhao , Xin Bian , Gaojin Li

A hallmark of intelligence is the ability to autonomously learn new flexible, cognitive behaviors - that is, behaviors where the appropriate action depends not just on immediate stimuli (as in simple reflexive stimulus-response…

Neural and Evolutionary Computing · Computer Science 2023-05-30 Thomas Miconi

Olfactory receptor usage is highly heterogeneous, with some receptor types being orders of magnitude more abundant than others. We propose an explanation for this striking fact: the receptor distribution is tuned to maximally represent…

Neurons and Cognition · Quantitative Biology 2019-01-23 Tiberiu Tesileanu , Simona Cocco , Remi Monasson , Vijay Balasubramanian

Fully autonomous mobile robots have a multitude of potential applications, but guaranteeing robust navigation performance remains an open research problem. For many tasks such as repeated infrastructure inspection, item delivery, or…

Robotics · Computer Science 2021-07-30 Dominic Dall'Osto , Tobias Fischer , Michael Milford

Thanks to recent technological advances, it is now possible to track with an unprecedented precision and for long periods of time the movement patterns of many living organisms in their habitat. The increasing amount of data available on…

Populations and Evolution · Quantitative Biology 2015-05-19 Denis Boyer , Peter D. Walsh

Inputs to signaling pathways can have complex statistics that depend on the environment and on the behavioral response to previous stimuli. Such behavioral feedback is particularly important in navigation. Successful navigation relies on…

Molecular Networks · Quantitative Biology 2014-12-02 Yann S. Dufour , Xiongfei Fu , Luis Hernandez-Nunez , Thierry Emonet

This paper presents Wanderer, a model of how autonomous adaptive systems coordinate internal biological needs with moment-by-moment assessments of the probabilities of events in the external world. The extent to which Wanderer moves about…

Neural and Evolutionary Computing · Computer Science 2019-07-11 Liane Gabora

The effects of fluid viscosity on the kinematics of a small swimmer at low Reynolds number are investigated in both experiments and in a simple model. The swimmer is the nematode Caenorhabditis elegans, which is an undulating roundworm…

Biological Physics · Physics 2009-12-18 Josue Sznitman , Xiaoning Shen , Prashant K Purohit , Paulo E Arratia

Sensory receptor neurons match their dynamic range to ecologically relevant stimulus intensities. How this tuning is achieved is poorly understood in most receptors. We show that in the C. elegans URX O2 sensing neurons two putative…

Neurons and Cognition · Quantitative Biology 2022-10-12 Shigekazu Oda , Yu Toyoshima , Mario de Bono

The aim of this paper is to study the reward based policy exploration problem in a supervised learning approach and enable robots to form complex movement trajectories in challenging reward settings and search spaces. For this, the…

Robotics · Computer Science 2020-11-10 M. Tuluhan Akbulut , Utku Bozdogan , Ahmet Tekden , Emre Ugur
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