Limits...
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.


Ecologically inspired interaction model, written in LCC, for agents coordination in an artificial ecosystem. The "visitor" role is specified in this section of the protocol.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3117761&req=5

Figure 14: Ecologically inspired interaction model, written in LCC, for agents coordination in an artificial ecosystem. The "visitor" role is specified in this section of the protocol.

Mentions: Figures 14 and 15 show the IM, written in LCC and based on the ecological concepts described above, that specifies the interactions between agents in our simulated ecosystem.


Automated experimentation in ecological networks.

Lurgi M, Robertson D - Autom Exp (2011)

Ecologically inspired interaction model, written in LCC, for agents coordination in an artificial ecosystem. The "visitor" role is specified in this section of the protocol.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 14: Ecologically inspired interaction model, written in LCC, for agents coordination in an artificial ecosystem. The "visitor" role is specified in this section of the protocol.
Mentions: Figures 14 and 15 show the IM, written in LCC and based on the ecological concepts described above, that specifies the interactions between agents in our simulated ecosystem.

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.