ArticleJournal of the Royal Society, Interface2019
Collective learning from individual experiences and information transfer during group foraging.
Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Uncovering complementary information sharing in spider monkey collective foraging using higher-order spatial networks.Npj complexity · 2026Article
- An Exploration of Individual and Collective Reversal Learning in Rats.Perspectives on behavior science · 2025Review
- An associative account of collective learning.Royal Society open science · 2025Article
- Disruption of collective behaviour correlates with reduced interaction efficiency.Proceedings. Biological sciences · 2025Article
- Article
- It's about time: Feeding competition costs of sociality are affected more by temporal characteristics than spatial distribution.Ecology and evolution · 2024Article
- Lévy movements and a slowly decaying memory allow efficient collective learning in groups of interacting foragers.PLoS computational biology · 2023Article
- Mechanisms of collective learning: how can animal groups improve collective performance when repeating a task?Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Neural networks reveal emergent properties of collective learning in democratic but not despotic groups.Animal behaviour · 2022Article
- Modelling collective navigation via non-local communication.Journal of the Royal Society, Interface · 2021Article
- Individual and collective foraging in autonomous search agents with human intervention.Scientific reports · 2021Article
- Balancing Collective Exploration and Exploitation in Multi-Agent and Multi-Robot Systems: A Review.Frontiers in robotics and AI · 2021Review
- Collective Computation in Animal Fission-Fusion Dynamics.Frontiers in robotics and AI · 2020Article
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Authors and funding
3 authors.
Funding
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Abstract
Living in groups brings benefits to many animals, such as 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 collective behaviours within animal groups on the move can be useful for pooling information about the current state of the environment. The effects of interactions on collective motion have been mostly studied in models of agents with no memory. Thus, whether coordinated behaviours can emerge from individuals with memory and different foraging experiences is still poorly understood. By means of an agent-based model, we quantify how individual memory and information fluxes can contribute to improving the foraging success of a group in complex environments. In this context, we define collective learning as a coordinated change of behaviour within a group resulting from individual experiences and information transfer. We show that an initially scattered population of foragers visiting dispersed resources can gradually achieve cohesion and become selectively localized in space around the most salient resource sites. Coordination is lost when memory or information transfer among individuals is suppressed. The present modelling framework provides predictions for empirical studies of collective learning and could also find applications in swarm robotics and motivate new search algorithms based on reinforcement.
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