Using Belief Theory to Formalize the Agent Behavior: Application to the Simulation of Avian Flu Propagation

Taillandier, Patrick; Amouroux, Edouard; Vo, Duc An; Olteanu‐Raimond, Ana‐Maria

doi:10.1007/978-3-642-25920-3_42

Cited by 1 publication

(1 citation statement)

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“…In most cases we find task oriented actors to be the most efficient and easy to understand implementation but many authors advocate explicitly programming different agent states [219] and some like to rely on the belief-intentdesire model [322][323][324]. Niches, incumbents, and regime resistance can be modelled with relative ease but should ideally not be represented by aggregates but by the individual actors that they consist of in reality.…”

Section: Agent-based Modellingmentioning

confidence: 99%

Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation

Hoekstra

Steinbuch

Verbong³

2017

Complexity

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The energy domain is still dominated by equilibrium models that underestimate both the dangers and opportunities related to climate change. In reality, climate and energy systems contain tipping points, feedback loops, and exponential developments. This paper describes how to create realistic energy transition management models: quantitative models that can discover profitable pathways from fossil fuels to renewable energy. We review the literature regarding agent-based economics, disruptive innovation, and transition management and determine the following requirements. Actors must be detailed, heterogeneous, interacting, learning, and strategizing. Technology should be represented as a detailed and heterogeneous portfolio that can develop in a bottom-up manner, using endogenous feedback loops. Assumptions about discount rates and the social cost of carbon should be configurable. The model should contain interactions between the global, national, local, and individual level. A review of modelling techniques shows that equilibrium models are unsuitable and that system dynamics and discrete event simulation are too limited. The agent-based approach is found to be uniquely suited for the complex adaptive sociotechnical systems that must be modelled. But the choice for agent-based models does not mean a rejection of other approaches because they can be accommodated within the agent-based framework. We conclude with practical guidelines.

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Section: Agent-based Modellingmentioning

confidence: 99%