Agent­Based modelling Sample Clauses

Agent­Based modelling. Agent-based modelling is a computer-supported tool to simulate complex interactions among different “agents”. In LOCAW, an agent-based model is a prototypical simulation of each organization, which includes different types of individuals with different organizational roles, their interactions – represented as a social network following certain rules of interaction that are based on both hierarchical and horizontal relationships, and the environment of the organization, formalized in dimensions such as regulations and structural dimensions. In LOCAW, the agent-based models had had the following goals: • To provide a formally represented model of each organisation, the interactions within it and with its environment, for automatic forecasting and policy planning. • To act as a test-bed for formalised assumptions of the drivers of and barriers to everyday pro-environmental behaviour, thus also being a tool for the integration of the different parts of the empirical research. • To explore the logical consequences of assumptions and evidence of the dynamics of everyday pro-environmental behaviour. • To allow the formalisation of the back-casting scenarios developed with case study partners and test different policy tracks derived from them, given the assumptions on key drivers and barriers of sustainable actions at work. Formal representations of each organisation and the interactions within it provide an internally consistent test-bed with which to examine the various ways scenario interventions affect overall system behaviour as an emergent property of interactions. These provide a ‘tool-to-think-with’, which may be used as part of wider discussions on the effectiveness of proposed measures. One advantage of agent-based modelling in this regard is that it can be used to make trials that would be infeasible, politically sensitive, or for some reason unethical if tested on a subgroup in the real world. The results of such tests, if evaluated with respect to the assumptions made by the model, could be useful in determining whether real-world trials should be attempted, or whether the expected effect of the proposed measure is likely to be insufficient to merit exploration outside the domain of the simulation. Agent-based modelling is also able to provide indicative outcomes from such scenarios, provided that the assumptions they embed are agreed. Unlike classical modelling (and in particular of physical systems), modelling social systems must be done with a sens...
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Related to Agent­Based modelling

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