ArticlePLoS computational biology2023
Lévy movements and a slowly decaying memory allow efficient collective learning in groups of interacting foragers.
Article in PLoS computational biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- A power-law tailed movement created by trajectory retracing.Biological cybernetics · 2026Article
- Supercharged penguins-supplementary feeding reshapes tawaki/Fiordland penguin winter migration.PeerJ · 2026Article
- An associative account of collective learning.Royal Society open science · 2025Article
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 2 countries.
Funding
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Abstract
Many animal species benefit from spatial learning to adapt their foraging movements to the distribution of resources. Learning involves the collection, storage and retrieval of information, and depends on both the random search strategies employed and the memory capacities of the individual. For animals living in social groups, spatial learning can be further enhanced by information transfer among group members. However, how individual behavior affects the emergence of collective states of learning is still poorly understood. Here, with the help of a spatially explicit agent-based model where individuals transfer information to their peers, we analyze the effects on the use of resources of varying memory capacities in combination with different exploration strategies, such as ordinary random walks and Lévy flights. We find that individual Lévy displacements associated with a slow memory decay lead to a very rapid collective response, a high group cohesion and to an optimal exploitation of the best resource patches in static but complex environments, even when the interaction rate among individuals is low.
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