2015
DOI: 10.1186/s40294-015-0007-2
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Dynamic agent composition for large-scale agent-based models

Abstract: Purpose: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. Methods:The dynamic agent composition approach consists in having agents, whose implementation has … Show more

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Cited by 14 publications
(7 citation statements)
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“…All actions and interactions are coupled and lead to emergent system dynamics: Agent A decided to perform action I, which hinders Agent B to perform action II but leads B to perform action III and eventually force the environmental layer agent to influence Agent A's future decision. The IPA framework handles all agent classes, the general composition of the modelled system and global model behaviour and is designed to manage agents in a dynamic way to allow the composition of large scale ABM models through the underlying GAMA architecture in headless mode to save computational time ( Taillandier et al 2012;Boulaire et al 2015).…”
Section: Framework Development For Agent-based Modelling Of Soil Watementioning
confidence: 99%
“…All actions and interactions are coupled and lead to emergent system dynamics: Agent A decided to perform action I, which hinders Agent B to perform action II but leads B to perform action III and eventually force the environmental layer agent to influence Agent A's future decision. The IPA framework handles all agent classes, the general composition of the modelled system and global model behaviour and is designed to manage agents in a dynamic way to allow the composition of large scale ABM models through the underlying GAMA architecture in headless mode to save computational time ( Taillandier et al 2012;Boulaire et al 2015).…”
Section: Framework Development For Agent-based Modelling Of Soil Watementioning
confidence: 99%
“…The control of CAS is highly dispersed and decentralized which needs to have a coherent behaviour (Armano and Javarone 2013). The overall behavior of the system is achieved by a huge number of decisions made by many individual agents in every moment in competition and cooperation among the agents themselves (Boulaire et al 2015). The analysis of CAS can be done by a combination of applied, theoretical and experimental methods, for example, mathematical modelling and computer-based simulation.…”
Section: Modelling Complex Adaptive Systemsmentioning
confidence: 99%
“…Agent-based models are models representing computer code, recursive mathematical rules, applied to a given well-defined set of inputs. ABM models are not restricted to represent general statistical models or driving equations of a system but can represent explicitly the micro interactions and patterns of behaviour of the agents (Boulaire et al 2015). Statistical and mathematical analysis techniques are still important as they play a critical role in developing and testing the ABM.…”
Section: Modelling Complex Adaptive Systemsmentioning
confidence: 99%
“…Agent-based models are the models which represent recursive mathematical functions, computer code that are applied to a definite set of inputs. These models can present explicitly the patterns of agent's behaviour, micro interactions and are not limited to drive equations of a system or representing general statistical models (Boulaire et al 2015). Mathematical and statistical analysis techniques still have importance in playing critical role in developing and testing the ABM.…”
Section: Modelling Complex Adaptive Systemsmentioning
confidence: 99%