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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.


Example of a complex food web in a real community (grassland in the United Kingdom). Nodes and edges (in the graph) represent species and trophic interactions among them respectively. (Image produced with FoodWeb3D, written by R.J. Williams and provided by the Pacific Ecoinformatics and Computational Ecology Lab http://www.foodwebs.org).
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Figure 2: Example of a complex food web in a real community (grassland in the United Kingdom). Nodes and edges (in the graph) represent species and trophic interactions among them respectively. (Image produced with FoodWeb3D, written by R.J. Williams and provided by the Pacific Ecoinformatics and Computational Ecology Lab http://www.foodwebs.org).

Mentions: In ecological networks the interactions between species in natural communities are represented in the form of a graph, where vertices and edges represent species and their relationships respectively. Figure 2 shows an example of a food web, a kind of ecological network in which the edges between species represent trophic relations, from a real community (a grassland in the United Kingdom). The representation of species in a community and their interactions thus facilitates the analyses of this kind of complex system. Ecological network research is concerned with the analysis of the relationships amongst species in an ecosystem from a network perspective, in order to determine community level features such as those described above for complex systems. These analyses have allowed scientists to better understand the organisational dynamics of the ecosystems represented by these entangled networks of interactions by establishing links between the dynamics occurring at the individual and species level to the structure of the network representing their relationships [8].


Automated experimentation in ecological networks.

Lurgi M, Robertson D - Autom Exp (2011)

Example of a complex food web in a real community (grassland in the United Kingdom). Nodes and edges (in the graph) represent species and trophic interactions among them respectively. (Image produced with FoodWeb3D, written by R.J. Williams and provided by the Pacific Ecoinformatics and Computational Ecology Lab http://www.foodwebs.org).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: Example of a complex food web in a real community (grassland in the United Kingdom). Nodes and edges (in the graph) represent species and trophic interactions among them respectively. (Image produced with FoodWeb3D, written by R.J. Williams and provided by the Pacific Ecoinformatics and Computational Ecology Lab http://www.foodwebs.org).
Mentions: In ecological networks the interactions between species in natural communities are represented in the form of a graph, where vertices and edges represent species and their relationships respectively. Figure 2 shows an example of a food web, a kind of ecological network in which the edges between species represent trophic relations, from a real community (a grassland in the United Kingdom). The representation of species in a community and their interactions thus facilitates the analyses of this kind of complex system. Ecological network research is concerned with the analysis of the relationships amongst species in an ecosystem from a network perspective, in order to determine community level features such as those described above for complex systems. These analyses have allowed scientists to better understand the organisational dynamics of the ecosystems represented by these entangled networks of interactions by establishing links between the dynamics occurring at the individual and species level to the structure of the network representing their relationships [8].

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.