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Automated experimentation in ecological networks.

Lurgi M, Robertson D - Autom Exp (2011)

Bottom Line: Interaction models for agents coordination thus engineered facilitate the emergence of network features such as those found in ecological networks of interacting species, in our artificial societies of agents.Agent based models developed in this way facilitate the automation of the design an execution of simulation experiments that allow for the exploration of diverse behavioural mechanisms believed to be responsible for community organisation in ecological communities.This automated way of conducting experiments empowers the study of ecological networks by exploiting the expressive power of interaction models specification in agent systems.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh, UK. miguel.lurgi@ed.ac.uk.

ABSTRACT

Background: In ecological networks, natural communities are studied from a complex systems perspective by representing interactions among species within them in the form of a graph, which is in turn analysed using mathematical tools. Topological features encountered in complex networks have been proved to provide the systems they represent with interesting attributes such as robustness and stability, which in ecological systems translates into the ability of communities to resist perturbations of different kinds. A focus of research in community ecology is on understanding the mechanisms by which these complex networks of interactions among species in a community arise. We employ an agent-based approach to model ecological processes operating at the species' interaction level for the study of the emergence of organisation in ecological networks.

Results: We have designed protocols of interaction among agents in a multi-agent system based on ecological processes occurring at the interaction level between species in plant-animal mutualistic communities. Interaction models for agents coordination thus engineered facilitate the emergence of network features such as those found in ecological networks of interacting species, in our artificial societies of agents.

Conclusions: Agent based models developed in this way facilitate the automation of the design an execution of simulation experiments that allow for the exploration of diverse behavioural mechanisms believed to be responsible for community organisation in ecological communities. This automated way of conducting experiments empowers the study of ecological networks by exploiting the expressive power of interaction models specification in agent systems.

No MeSH data available.


Related in: MedlinePlus

Examples of mutualistic relationships in nature. From left to right: plant-pollinator interaction between a bee and a flower, plant-frugivore interaction between a bird and a fleshy fruit plant, and mutualistic association between fungi and algae (i.e. a lichen).
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Figure 1: Examples of mutualistic relationships in nature. From left to right: plant-pollinator interaction between a bee and a flower, plant-frugivore interaction between a bird and a fleshy fruit plant, and mutualistic association between fungi and algae (i.e. a lichen).

Mentions: Mutualistic relationships are ubiquitous in nature (Figure 1), ranging from the interactions between plants and their animal pollinators or seed dispersers, without which life on Earth could seldom be imagined, to the complex association between fungi and algae that form lichens. All these interactions have arisen in nature because they represent an important advantage for the individuals taking part on them, and moreover, in some cases, one or both of the interacting partners would not be able to survive outside the interaction.


Automated experimentation in ecological networks.

Lurgi M, Robertson D - Autom Exp (2011)

Examples of mutualistic relationships in nature. From left to right: plant-pollinator interaction between a bee and a flower, plant-frugivore interaction between a bird and a fleshy fruit plant, and mutualistic association between fungi and algae (i.e. a lichen).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3117761&req=5

Figure 1: Examples of mutualistic relationships in nature. From left to right: plant-pollinator interaction between a bee and a flower, plant-frugivore interaction between a bird and a fleshy fruit plant, and mutualistic association between fungi and algae (i.e. a lichen).
Mentions: Mutualistic relationships are ubiquitous in nature (Figure 1), ranging from the interactions between plants and their animal pollinators or seed dispersers, without which life on Earth could seldom be imagined, to the complex association between fungi and algae that form lichens. All these interactions have arisen in nature because they represent an important advantage for the individuals taking part on them, and moreover, in some cases, one or both of the interacting partners would not be able to survive outside the interaction.

Bottom Line: Interaction models for agents coordination thus engineered facilitate the emergence of network features such as those found in ecological networks of interacting species, in our artificial societies of agents.Agent based models developed in this way facilitate the automation of the design an execution of simulation experiments that allow for the exploration of diverse behavioural mechanisms believed to be responsible for community organisation in ecological communities.This automated way of conducting experiments empowers the study of ecological networks by exploiting the expressive power of interaction models specification in agent systems.

View Article: PubMed Central - HTML - PubMed

Affiliation: School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh, UK. miguel.lurgi@ed.ac.uk.

ABSTRACT

Background: In ecological networks, natural communities are studied from a complex systems perspective by representing interactions among species within them in the form of a graph, which is in turn analysed using mathematical tools. Topological features encountered in complex networks have been proved to provide the systems they represent with interesting attributes such as robustness and stability, which in ecological systems translates into the ability of communities to resist perturbations of different kinds. A focus of research in community ecology is on understanding the mechanisms by which these complex networks of interactions among species in a community arise. We employ an agent-based approach to model ecological processes operating at the species' interaction level for the study of the emergence of organisation in ecological networks.

Results: We have designed protocols of interaction among agents in a multi-agent system based on ecological processes occurring at the interaction level between species in plant-animal mutualistic communities. Interaction models for agents coordination thus engineered facilitate the emergence of network features such as those found in ecological networks of interacting species, in our artificial societies of agents.

Conclusions: Agent based models developed in this way facilitate the automation of the design an execution of simulation experiments that allow for the exploration of diverse behavioural mechanisms believed to be responsible for community organisation in ecological communities. This automated way of conducting experiments empowers the study of ecological networks by exploiting the expressive power of interaction models specification in agent systems.

No MeSH data available.


Related in: MedlinePlus