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In this paper, we study a probabilistic reinforcement-learning model for ants searching for the shortest path(s) between their nest and a source of food. In this model, the nest and the source of food are two distinguished nodes $N$ and $F$…

Probability · Mathematics 2023-10-03 Daniel Kious , Cécile Mailler , Bruno Schapira

Ants are known to be able to find paths of minimal length between the nest and food sources. The deposit of pheromones while they search for food and their chemotactical response to them has been proposed as a crucial element in the…

Populations and Evolution · Quantitative Biology 2011-03-09 M. Vela-Pérez , M. A. Fontelos , J. J. L. Velázquez

The ants process is a stochastic process introduced by Kious, Mailler and Schapira as a model for the phenomenon of ants finding shortest paths between their nest and a source of food (seen as two marked nodes in a finite graph), with no…

Probability · Mathematics 2026-02-02 Cécile Mailler , Zoé Varin

Colonies of the arboreal turtle ant create networks of trails that link nests and food sources on the graph formed by branches and vines in the canopy of the tropical forest. Ants put down a volatile pheromone on edges as they traverse…

Data Structures and Algorithms · Computer Science 2023-07-04 Shivam Garg , Kirankumar Shiragur , Deborah M. Gordon , Moses Charikar

Many ant species employ distributed population density estimation in applications ranging from quorum sensing [Pra05], to task allocation [Gor99], to appraisal of enemy colony strength [Ada90]. It has been shown that ants estimate density…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-06-08 Cameron Musco , Hsin-Hao Su , Nancy Lynch

We consider discrete dynamical systems of "ant-like" agents engaged in a sequence of pursuits on a graph environment. The agents emerge one by one at equal time intervals from a source vertex $s$ and pursue each other by greedily attempting…

Discrete Mathematics · Computer Science 2019-08-09 Michael Amir , Alfred M. Bruckstein

Colonies of ants are systems of interacting living organisms in which interactions between individuals and their environment can produce a reliable performance of a complex tasks without the need for centralised control. Particularly…

Biological Physics · Physics 2015-08-28 Miriam Malíčková , Christian Yates , Katarína Boďová

In this paper we introduce a new simple but powerful general technique for the study of edge- and vertex-reinforced processes with super-linear reinforcement, based on the use of order statistics for the number of edge, respectively of…

Probability · Mathematics 2016-06-03 Codina Cotar , Debleena Thacker

Ant raiding, the process of identifying and returning food to the nest or bivouac, is a fascinating example of collective motion in nature. During such raids ants lay pheromones to form trails for others to find a food source. In this work…

Adaptation and Self-Organizing Systems · Physics 2015-08-18 Shawn D. Ryan

Under certain circumstances, a swarm of a species of trail-laying ants known as army ants can become caught in a doomed revolving motion known as the death spiral, in which each ant follows the one in front of it in a never-ending loop…

Analysis of PDEs · Mathematics 2017-03-21 Ria Das

The co-evolution between network structure and functional performance is a fundamental and challenging problem whose complexity emerges from the intrinsic interdependent nature of structure and function. Within this context, we investigate…

Neural and Evolutionary Computing · Computer Science 2016-05-10 Daniel R. Figueiredo , Michele Garetto

Random walks constitute a fundamental mechanism for a large set of dynamics taking place on networks. In this article, we study random walks on weighted networks with an arbitrary degree distribution, where the weight of an edge between two…

Statistical Mechanics · Physics 2013-01-17 Zhongzhi Zhang , Tong Shan , Guanrong Chen

Graph embedding methods represent nodes in a continuous vector space, preserving information from the graph (e.g. by sampling random walks). There are many hyper-parameters to these methods (such as random walk length) which have to be…

Machine Learning · Computer Science 2018-12-27 Sami Abu-El-Haija , Bryan Perozzi , Rami Al-Rfou , Alex Alemi

Graph embedding has recently gained momentum in the research community, in particular after the introduction of random walk and neural network based approaches. However, most of the embedding approaches focus on representing the local…

Machine Learning · Computer Science 2020-02-19 Joerg Schloetterer , Martin Wehking , Fatemeh Salehi Rizi , Michael Granitzer

Over the years, many approaches have been proposed to build ancestral recombination graphs (ARGs), graphs used to represent the genetic relationship between individuals. Among these methods, many rely on the assumption that the most likely…

Machine Learning · Computer Science 2025-06-16 Mélanie Raymond , Marie-Hélène Descary , Cédric Beaulac , Fabrice Larribe

We propose a model of network formation based on reinforcement learning, which can be seen as a generalization as the one proposed by Skyrms for signaling games. On a discrete graph, whose vertices represent individuals, at any time step…

Probability · Mathematics 2016-02-08 Daniel Kious , Pierre Tarrès

We study random walk with adaptive move strategies on a class of directed graphs with variable wiring diagram. The graphs are grown from the evolution rules compatible with the dynamics of the world-wide Web [Tadi\'c, Physica A {\bf 293},…

Statistical Mechanics · Physics 2009-11-07 Bosiljka Tadic

Single particle tracking allows probing how biomolecules interact physically with their natural environments. A fundamental challenge when analysing recorded single particle trajectories is the inverse problem of inferring the physical…

Navigation through narrow passages during colony relocation by the tandem-running ants, $\textit{Diacamma}$ $\textit{indicum}$, is a tour de force of biological traffic coordination. Even on one-lane paths, the ants tactfully manage a…

Adaptation and Self-Organizing Systems · Physics 2025-09-23 Joy Das Bairagya , Udipta Chakraborti , Sumana Annagiri , Sagar Chakraborty

Many network analysis and graph learning techniques are based on models of random walks which require to infer transition matrices that formalize the underlying stochastic process in an observed graph. For weighted graphs, it is common to…

Methodology · Statistics 2022-10-28 Vincenzo Perri , Luka V. Petrović , Ingo Scholtes
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