Abstract
Our aim is to demonstrate how agent-based motivation models can play a role in the process of policy making and implementation. In this paper, we describe how the motivation models support the description of desirable outcomes and help to develop relevant high-level goals in policy making in particularly complex areas. We give two example domains where we have developed agent-based models. The first is data management policy for university researchers. The second one focuses on sustainable households, and how to provide relevant guidance for educating people and helping them to understand how to behave in a more environmentally friendly manner. Our two examples demonstrate that the agent-based models are able to help to come up with shared quality goals and identifying the right stakeholders in these two multifaceted and abstract domains. We aim to enable people involved in policy making to focus on and understand the relevant goals, quality goals and activities in order to formulate effective and supportive policies that can accomplish the intended outcomes.
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Pedell, S., Sterling, L. (2012). The Benefits of Agent-Based Motivation Models in Policy Formulation and Implementation. In: Dechesne, F., Hattori, H., ter Mors, A., Such, J.M., Weyns, D., Dignum, F. (eds) Advanced Agent Technology. AAMAS 2011. Lecture Notes in Computer Science(), vol 7068. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27216-5_9
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DOI: https://doi.org/10.1007/978-3-642-27216-5_9
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