Open access
Author
Date
2018-12Type
- Journal Article
Abstract
Collective sensing is an emergent phenomenon which enables individuals to estimate a hidden property of the environment through the observation of social interactions. Previous work on collective sensing shows that gregarious individuals obtain an evolutionary advantage by exploiting collective sensing when competing against solitary individuals. This work addresses the question of whether collective sensing allows for the emergence of groups from a population of individuals without predetermined behaviors. It is assumed that group membership does not lessen competition on the limited resources in the environment, e.g., groups do not improve foraging efficiency. Experiments are run in an agent-based evolutionary model of a foraging task, where the fitness of the agents depends on their foraging strategy. The foraging strategy of agents is determined by a neural network, which does not require explicit modeling of the environment and of the interactions between agents. Experiments demonstrate that gregarious behavior is not the evolutionary-fittest strategy if resources are abundant, thus invalidating previous findings in a specific region of the parameter space. In other words, resource scarcity makes gregarious behavior so valuable as to make up for the increased competition over the few available resources. Furthermore, it is shown that a population of solitary agents can evolve gregarious behavior in response to a sudden scarcity of resources, thus individuating a possible mechanism that leads to gregarious behavior in nature. The evolutionary process operates on the whole parameter space of the neural networks; hence, these behaviors are selected among an unconstrained set of behavioral models. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000246194Publication status
publishedExternal links
Journal / series
Swarm IntelligenceVolume
Pages / Article No.
Publisher
SpringerSubject
Collective sensing; Natural selection; Foraging; Agent-based modeling; Multi-agent systems; Neural networkOrganisational unit
03784 - Helbing, Dirk / Helbing, Dirk
Funding
324247 - Modeling the Emergence of Social Complexity and Order: How Individual and Societal Complexity Co-Evolve (EC)
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