Conclusion

Adaptive agents are software entities in a model that are goal oriented and have the capacity to adapt their comportment as a function of environmental stimuli. Adaptive agents are used in a wide range of fields to find solutions to problems that benefit from parallel processing. The parallel actions of many agents can lead to the emergence of multiple solutions, or of solutions that may not have been found via more linear methods. The adaptive nature of agents allows for the simulation of realistic social interactions and of the emergence of complex social hierarchies and group-level behavior. In the field of ecological informatics, adaptive agents can be applied to study how complex social structures can emerge via the combined interactions of lower-level components. This approach to modeling in ecology forms a useful addition to the toolbox of bottom-up methods inspired from complex systems science.

See also: Application of Ecological Informatics; Artificial Neural Networks; Cellular Automata; Ecological Complexity; Ecological Informatics: Overview; Evolutionary Algorithms; Individual-Based Models.

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